diff --git a/02_activities/assignments/assignment_1.ipynb b/02_activities/assignments/assignment_1.ipynb
index 28d4df017..9151feaf9 100644
--- a/02_activities/assignments/assignment_1.ipynb
+++ b/02_activities/assignments/assignment_1.ipynb
@@ -34,7 +34,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "id": "4a3485d6-ba58-4660-a983-5680821c5719",
    "metadata": {},
    "outputs": [],
@@ -56,10 +56,288 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "id": "a431d282-f9ca-4d5d-8912-71ffc9d8ea19",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>alcohol</th>\n",
+       "      <th>malic_acid</th>\n",
+       "      <th>ash</th>\n",
+       "      <th>alcalinity_of_ash</th>\n",
+       "      <th>magnesium</th>\n",
+       "      <th>total_phenols</th>\n",
+       "      <th>flavanoids</th>\n",
+       "      <th>nonflavanoid_phenols</th>\n",
+       "      <th>proanthocyanins</th>\n",
+       "      <th>color_intensity</th>\n",
+       "      <th>hue</th>\n",
+       "      <th>od280/od315_of_diluted_wines</th>\n",
+       "      <th>proline</th>\n",
+       "      <th>class</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>14.23</td>\n",
+       "      <td>1.71</td>\n",
+       "      <td>2.43</td>\n",
+       "      <td>15.6</td>\n",
+       "      <td>127.0</td>\n",
+       "      <td>2.80</td>\n",
+       "      <td>3.06</td>\n",
+       "      <td>0.28</td>\n",
+       "      <td>2.29</td>\n",
+       "      <td>5.64</td>\n",
+       "      <td>1.04</td>\n",
+       "      <td>3.92</td>\n",
+       "      <td>1065.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>13.20</td>\n",
+       "      <td>1.78</td>\n",
+       "      <td>2.14</td>\n",
+       "      <td>11.2</td>\n",
+       "      <td>100.0</td>\n",
+       "      <td>2.65</td>\n",
+       "      <td>2.76</td>\n",
+       "      <td>0.26</td>\n",
+       "      <td>1.28</td>\n",
+       "      <td>4.38</td>\n",
+       "      <td>1.05</td>\n",
+       "      <td>3.40</td>\n",
+       "      <td>1050.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>13.16</td>\n",
+       "      <td>2.36</td>\n",
+       "      <td>2.67</td>\n",
+       "      <td>18.6</td>\n",
+       "      <td>101.0</td>\n",
+       "      <td>2.80</td>\n",
+       "      <td>3.24</td>\n",
+       "      <td>0.30</td>\n",
+       "      <td>2.81</td>\n",
+       "      <td>5.68</td>\n",
+       "      <td>1.03</td>\n",
+       "      <td>3.17</td>\n",
+       "      <td>1185.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>14.37</td>\n",
+       "      <td>1.95</td>\n",
+       "      <td>2.50</td>\n",
+       "      <td>16.8</td>\n",
+       "      <td>113.0</td>\n",
+       "      <td>3.85</td>\n",
+       "      <td>3.49</td>\n",
+       "      <td>0.24</td>\n",
+       "      <td>2.18</td>\n",
+       "      <td>7.80</td>\n",
+       "      <td>0.86</td>\n",
+       "      <td>3.45</td>\n",
+       "      <td>1480.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>13.24</td>\n",
+       "      <td>2.59</td>\n",
+       "      <td>2.87</td>\n",
+       "      <td>21.0</td>\n",
+       "      <td>118.0</td>\n",
+       "      <td>2.80</td>\n",
+       "      <td>2.69</td>\n",
+       "      <td>0.39</td>\n",
+       "      <td>1.82</td>\n",
+       "      <td>4.32</td>\n",
+       "      <td>1.04</td>\n",
+       "      <td>2.93</td>\n",
+       "      <td>735.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>173</th>\n",
+       "      <td>13.71</td>\n",
+       "      <td>5.65</td>\n",
+       "      <td>2.45</td>\n",
+       "      <td>20.5</td>\n",
+       "      <td>95.0</td>\n",
+       "      <td>1.68</td>\n",
+       "      <td>0.61</td>\n",
+       "      <td>0.52</td>\n",
+       "      <td>1.06</td>\n",
+       "      <td>7.70</td>\n",
+       "      <td>0.64</td>\n",
+       "      <td>1.74</td>\n",
+       "      <td>740.0</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>174</th>\n",
+       "      <td>13.40</td>\n",
+       "      <td>3.91</td>\n",
+       "      <td>2.48</td>\n",
+       "      <td>23.0</td>\n",
+       "      <td>102.0</td>\n",
+       "      <td>1.80</td>\n",
+       "      <td>0.75</td>\n",
+       "      <td>0.43</td>\n",
+       "      <td>1.41</td>\n",
+       "      <td>7.30</td>\n",
+       "      <td>0.70</td>\n",
+       "      <td>1.56</td>\n",
+       "      <td>750.0</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>175</th>\n",
+       "      <td>13.27</td>\n",
+       "      <td>4.28</td>\n",
+       "      <td>2.26</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>120.0</td>\n",
+       "      <td>1.59</td>\n",
+       "      <td>0.69</td>\n",
+       "      <td>0.43</td>\n",
+       "      <td>1.35</td>\n",
+       "      <td>10.20</td>\n",
+       "      <td>0.59</td>\n",
+       "      <td>1.56</td>\n",
+       "      <td>835.0</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>176</th>\n",
+       "      <td>13.17</td>\n",
+       "      <td>2.59</td>\n",
+       "      <td>2.37</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>120.0</td>\n",
+       "      <td>1.65</td>\n",
+       "      <td>0.68</td>\n",
+       "      <td>0.53</td>\n",
+       "      <td>1.46</td>\n",
+       "      <td>9.30</td>\n",
+       "      <td>0.60</td>\n",
+       "      <td>1.62</td>\n",
+       "      <td>840.0</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>177</th>\n",
+       "      <td>14.13</td>\n",
+       "      <td>4.10</td>\n",
+       "      <td>2.74</td>\n",
+       "      <td>24.5</td>\n",
+       "      <td>96.0</td>\n",
+       "      <td>2.05</td>\n",
+       "      <td>0.76</td>\n",
+       "      <td>0.56</td>\n",
+       "      <td>1.35</td>\n",
+       "      <td>9.20</td>\n",
+       "      <td>0.61</td>\n",
+       "      <td>1.60</td>\n",
+       "      <td>560.0</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>178 rows × 14 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     alcohol  malic_acid   ash  alcalinity_of_ash  magnesium  total_phenols  \\\n",
+       "0      14.23        1.71  2.43               15.6      127.0           2.80   \n",
+       "1      13.20        1.78  2.14               11.2      100.0           2.65   \n",
+       "2      13.16        2.36  2.67               18.6      101.0           2.80   \n",
+       "3      14.37        1.95  2.50               16.8      113.0           3.85   \n",
+       "4      13.24        2.59  2.87               21.0      118.0           2.80   \n",
+       "..       ...         ...   ...                ...        ...            ...   \n",
+       "173    13.71        5.65  2.45               20.5       95.0           1.68   \n",
+       "174    13.40        3.91  2.48               23.0      102.0           1.80   \n",
+       "175    13.27        4.28  2.26               20.0      120.0           1.59   \n",
+       "176    13.17        2.59  2.37               20.0      120.0           1.65   \n",
+       "177    14.13        4.10  2.74               24.5       96.0           2.05   \n",
+       "\n",
+       "     flavanoids  nonflavanoid_phenols  proanthocyanins  color_intensity   hue  \\\n",
+       "0          3.06                  0.28             2.29             5.64  1.04   \n",
+       "1          2.76                  0.26             1.28             4.38  1.05   \n",
+       "2          3.24                  0.30             2.81             5.68  1.03   \n",
+       "3          3.49                  0.24             2.18             7.80  0.86   \n",
+       "4          2.69                  0.39             1.82             4.32  1.04   \n",
+       "..          ...                   ...              ...              ...   ...   \n",
+       "173        0.61                  0.52             1.06             7.70  0.64   \n",
+       "174        0.75                  0.43             1.41             7.30  0.70   \n",
+       "175        0.69                  0.43             1.35            10.20  0.59   \n",
+       "176        0.68                  0.53             1.46             9.30  0.60   \n",
+       "177        0.76                  0.56             1.35             9.20  0.61   \n",
+       "\n",
+       "     od280/od315_of_diluted_wines  proline  class  \n",
+       "0                            3.92   1065.0      0  \n",
+       "1                            3.40   1050.0      0  \n",
+       "2                            3.17   1185.0      0  \n",
+       "3                            3.45   1480.0      0  \n",
+       "4                            2.93    735.0      0  \n",
+       "..                            ...      ...    ...  \n",
+       "173                          1.74    740.0      2  \n",
+       "174                          1.56    750.0      2  \n",
+       "175                          1.56    835.0      2  \n",
+       "176                          1.62    840.0      2  \n",
+       "177                          1.60    560.0      2  \n",
+       "\n",
+       "[178 rows x 14 columns]"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "from sklearn.datasets import load_wine\n",
     "\n",
@@ -91,12 +369,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "id": "56916892",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "178\n"
+     ]
+    }
+   ],
    "source": [
-    "# Your answer here"
+    "count_row = wine_df.shape[0] # See https://www.w3schools.com/datascience/ds_python_dataframe.asp\n",
+    "print(count_row)"
    ]
   },
   {
@@ -109,12 +396,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "id": "df0ef103",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "14\n"
+     ]
+    }
+   ],
    "source": [
-    "# Your answer here"
+    "count_column = wine_df.shape[1]\n",
+    "print(count_column)"
    ]
   },
   {
@@ -127,12 +423,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "id": "47989426",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "class\n",
+       "1    71\n",
+       "0    59\n",
+       "2    48\n",
+       "Name: count, dtype: int64"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# Your answer here"
+    "wine_df[\"class\"].value_counts()\n"
    ]
   },
   {
@@ -149,9 +460,17 @@
    "execution_count": null,
    "id": "bd7b0910",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "13\n"
+     ]
+    }
+   ],
    "source": [
-    "# Your answer here"
+    "print((count_column) - 1) # Exclude the one class variable "
    ]
   },
   {
@@ -175,10 +494,37 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 7,
    "id": "cc899b59",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "    alcohol  malic_acid       ash  alcalinity_of_ash  magnesium  \\\n",
+      "0  1.518613   -0.562250  0.232053          -1.169593   1.913905   \n",
+      "1  0.246290   -0.499413 -0.827996          -2.490847   0.018145   \n",
+      "2  0.196879    0.021231  1.109334          -0.268738   0.088358   \n",
+      "3  1.691550   -0.346811  0.487926          -0.809251   0.930918   \n",
+      "4  0.295700    0.227694  1.840403           0.451946   1.281985   \n",
+      "\n",
+      "   total_phenols  flavanoids  nonflavanoid_phenols  proanthocyanins  \\\n",
+      "0       0.808997    1.034819             -0.659563         1.224884   \n",
+      "1       0.568648    0.733629             -0.820719        -0.544721   \n",
+      "2       0.808997    1.215533             -0.498407         2.135968   \n",
+      "3       2.491446    1.466525             -0.981875         1.032155   \n",
+      "4       0.808997    0.663351              0.226796         0.401404   \n",
+      "\n",
+      "   color_intensity       hue  od280/od315_of_diluted_wines   proline  \n",
+      "0         0.251717  0.362177                      1.847920  1.013009  \n",
+      "1        -0.293321  0.406051                      1.113449  0.965242  \n",
+      "2         0.269020  0.318304                      0.788587  1.395148  \n",
+      "3         1.186068 -0.427544                      1.184071  2.334574  \n",
+      "4        -0.319276  0.362177                      0.449601 -0.037874  \n"
+     ]
+    }
+   ],
    "source": [
     "# Select predictors (excluding the last column)\n",
     "predictors = wine_df.iloc[:, :-1]\n",
@@ -204,7 +550,7 @@
    "id": "403ef0bb",
    "metadata": {},
    "source": [
-    "> Your answer here..."
+    "> The measurement scales for the predictor variables differ. Therefore, it is necessary to standardize (i.e., scale and centre) the predictor variables to ensure that the model's input values influence KNN machine learning modeling classification outcomes in proportion to the predictors' relative (distance) values. KNN modeling uses distance measures between selected neighbouring datapoints, and as such, the absolute scale of the predictor variables would influence the relative Euclidian straight-line distance among datapoints such that unstandardized predictor variables with relatively larger scale measures would dominate and disproportionately contribute to the modeling predictions.   "
    ]
   },
   {
@@ -220,7 +566,7 @@
    "id": "fdee5a15",
    "metadata": {},
    "source": [
-    "> Your answer here..."
+    "> The variable wine \"Class\" is a single, categorical (i.e., nominal) KNN modeling outcome variable. Standardizing a classifier variable label does not make sense because there is no \"scale\" associated with a nominal value. Moreover, KNN modeling only calculates the distance amoung selected neighbouring datapoints, not between the classifier variable labels. "
    ]
   },
   {
@@ -236,7 +582,7 @@
    "id": "f0676c21",
    "metadata": {},
    "source": [
-    "> Your answer here..."
+    "> In Python, the random number generator function relies on a single, arbitrary seed (integer) input value to generate a sequence of random numbers for a machine learning model algorithm such as KNN modeling. The seed value selected determines how the dataset observations are split between the training and testing sets, and between the training subsets. But for any particular seed value, the split is identical each time the model is run, ensuring reproducible results on the training and test trials. The particular seed values selected does not matter because regardless of how the observations are split in the dataset, the originating dataset is the same and therefore the results are consistent across seed input values."
    ]
   },
   {
@@ -261,7 +607,79 @@
     "\n",
     "# split the data into a training and testing set. hint: use train_test_split !\n",
     "\n",
-    "# Your code here ..."
+    "# Note that I relied on the question asked by Hannah Shuster-Hyman in the Slack channel, and on Dmytro Bonislavskyi's response, to approach this question. \n",
+    "# Also:  https://scikit-learn.org/stable/modules/cross_validation.html#cross-validation for content\n",
+    "# & https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.train_test_split.html#sklearn.model_selection.train_test_split for syntax \n",
+    "X_train, X_test, y_train, y_test = train_test_split(\n",
+    "    predictors_standardized,\n",
+    "    wine_df[\"class\"],\n",
+    "    train_size=0.75,\n",
+    "    stratify = wine_df[\"class\"]\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "7fd14f34",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "Index: 133 entries, 78 to 66\n",
+      "Data columns (total 13 columns):\n",
+      " #   Column                        Non-Null Count  Dtype  \n",
+      "---  ------                        --------------  -----  \n",
+      " 0   alcohol                       133 non-null    float64\n",
+      " 1   malic_acid                    133 non-null    float64\n",
+      " 2   ash                           133 non-null    float64\n",
+      " 3   alcalinity_of_ash             133 non-null    float64\n",
+      " 4   magnesium                     133 non-null    float64\n",
+      " 5   total_phenols                 133 non-null    float64\n",
+      " 6   flavanoids                    133 non-null    float64\n",
+      " 7   nonflavanoid_phenols          133 non-null    float64\n",
+      " 8   proanthocyanins               133 non-null    float64\n",
+      " 9   color_intensity               133 non-null    float64\n",
+      " 10  hue                           133 non-null    float64\n",
+      " 11  od280/od315_of_diluted_wines  133 non-null    float64\n",
+      " 12  proline                       133 non-null    float64\n",
+      "dtypes: float64(13)\n",
+      "memory usage: 14.5 KB\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Check number and which observations are in the X training set\n",
+    "X_train.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "c6afdf86",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.series.Series'>\n",
+      "Index: 133 entries, 78 to 66\n",
+      "Series name: class\n",
+      "Non-Null Count  Dtype\n",
+      "--------------  -----\n",
+      "133 non-null    int64\n",
+      "dtypes: int64(1)\n",
+      "memory usage: 2.1 KB\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Check number and which observations are in the y training set\n",
+    "y_train.info()"
    ]
   },
   {
@@ -284,12 +702,2321 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 11,
    "id": "08818c64",
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here..."
+    "# Initialize the KNN classifier\n",
+    "knn = KNeighborsClassifier()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "d80c1a84",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Grid search to find the optimal value of k that we want to model: create a parameter_grid library\n",
+    "parameter_grid = {\n",
+    "    \"n_neighbors\": range(1, 51)\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "627699a5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Initialize GridSearchCV object with a 10-fold cross-validation\n",
+    "wine_tune_grid = GridSearchCV(\n",
+    "    estimator = knn,\n",
+    "    param_grid = parameter_grid,\n",
+    "    cv = 10\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "5319512e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<style>#sk-container-id-1 {\n",
+       "  /* Definition of color scheme common for light and dark mode */\n",
+       "  --sklearn-color-text: #000;\n",
+       "  --sklearn-color-text-muted: #666;\n",
+       "  --sklearn-color-line: gray;\n",
+       "  /* Definition of color scheme for unfitted estimators */\n",
+       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
+       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
+       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
+       "  --sklearn-color-unfitted-level-3: chocolate;\n",
+       "  /* Definition of color scheme for fitted estimators */\n",
+       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
+       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
+       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
+       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
+       "\n",
+       "  /* Specific color for light theme */\n",
+       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
+       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+       "  --sklearn-color-icon: #696969;\n",
+       "\n",
+       "  @media (prefers-color-scheme: dark) {\n",
+       "    /* Redefinition of color scheme for dark theme */\n",
+       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
+       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+       "    --sklearn-color-icon: #878787;\n",
+       "  }\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 pre {\n",
+       "  padding: 0;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 input.sk-hidden--visually {\n",
+       "  border: 0;\n",
+       "  clip: rect(1px 1px 1px 1px);\n",
+       "  clip: rect(1px, 1px, 1px, 1px);\n",
+       "  height: 1px;\n",
+       "  margin: -1px;\n",
+       "  overflow: hidden;\n",
+       "  padding: 0;\n",
+       "  position: absolute;\n",
+       "  width: 1px;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-dashed-wrapped {\n",
+       "  border: 1px dashed var(--sklearn-color-line);\n",
+       "  margin: 0 0.4em 0.5em 0.4em;\n",
+       "  box-sizing: border-box;\n",
+       "  padding-bottom: 0.4em;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-container {\n",
+       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+       "     so we also need the `!important` here to be able to override the\n",
+       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+       "  display: inline-block !important;\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-text-repr-fallback {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-parallel-item,\n",
+       "div.sk-serial,\n",
+       "div.sk-item {\n",
+       "  /* draw centered vertical line to link estimators */\n",
+       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+       "  background-size: 2px 100%;\n",
+       "  background-repeat: no-repeat;\n",
+       "  background-position: center center;\n",
+       "}\n",
+       "\n",
+       "/* Parallel-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-1 div.sk-parallel-item::after {\n",
+       "  content: \"\";\n",
+       "  width: 100%;\n",
+       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+       "  flex-grow: 1;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-parallel {\n",
+       "  display: flex;\n",
+       "  align-items: stretch;\n",
+       "  justify-content: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-parallel-item {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-parallel-item:first-child::after {\n",
+       "  align-self: flex-end;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-parallel-item:last-child::after {\n",
+       "  align-self: flex-start;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-parallel-item:only-child::after {\n",
+       "  width: 0;\n",
+       "}\n",
+       "\n",
+       "/* Serial-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-1 div.sk-serial {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "  align-items: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  padding-right: 1em;\n",
+       "  padding-left: 1em;\n",
+       "}\n",
+       "\n",
+       "\n",
+       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+       "clickable and can be expanded/collapsed.\n",
+       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
+       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+       "*/\n",
+       "\n",
+       "/* Pipeline and ColumnTransformer style (default) */\n",
+       "\n",
+       "#sk-container-id-1 div.sk-toggleable {\n",
+       "  /* Default theme specific background. It is overwritten whether we have a\n",
+       "  specific estimator or a Pipeline/ColumnTransformer */\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable label */\n",
+       "#sk-container-id-1 label.sk-toggleable__label {\n",
+       "  cursor: pointer;\n",
+       "  display: flex;\n",
+       "  width: 100%;\n",
+       "  margin-bottom: 0;\n",
+       "  padding: 0.5em;\n",
+       "  box-sizing: border-box;\n",
+       "  text-align: center;\n",
+       "  align-items: start;\n",
+       "  justify-content: space-between;\n",
+       "  gap: 0.5em;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 label.sk-toggleable__label .caption {\n",
+       "  font-size: 0.6rem;\n",
+       "  font-weight: lighter;\n",
+       "  color: var(--sklearn-color-text-muted);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 label.sk-toggleable__label-arrow:before {\n",
+       "  /* Arrow on the left of the label */\n",
+       "  content: \"▸\";\n",
+       "  float: left;\n",
+       "  margin-right: 0.25em;\n",
+       "  color: var(--sklearn-color-icon);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable content - dropdown */\n",
+       "\n",
+       "#sk-container-id-1 div.sk-toggleable__content {\n",
+       "  display: none;\n",
+       "  text-align: left;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-toggleable__content.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-toggleable__content pre {\n",
+       "  margin: 0.2em;\n",
+       "  border-radius: 0.25em;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-toggleable__content.fitted pre {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+       "  /* Expand drop-down */\n",
+       "  display: block;\n",
+       "  width: 100%;\n",
+       "  overflow: visible;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+       "  content: \"▾\";\n",
+       "}\n",
+       "\n",
+       "/* Pipeline/ColumnTransformer-specific style */\n",
+       "\n",
+       "#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific style */\n",
+       "\n",
+       "/* Colorize estimator box */\n",
+       "#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-label label.sk-toggleable__label,\n",
+       "#sk-container-id-1 div.sk-label label {\n",
+       "  /* The background is the default theme color */\n",
+       "  color: var(--sklearn-color-text-on-default-background);\n",
+       "}\n",
+       "\n",
+       "/* On hover, darken the color of the background */\n",
+       "#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Label box, darken color on hover, fitted */\n",
+       "#sk-container-id-1 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator label */\n",
+       "\n",
+       "#sk-container-id-1 div.sk-label label {\n",
+       "  font-family: monospace;\n",
+       "  font-weight: bold;\n",
+       "  display: inline-block;\n",
+       "  line-height: 1.2em;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-label-container {\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific */\n",
+       "#sk-container-id-1 div.sk-estimator {\n",
+       "  font-family: monospace;\n",
+       "  border: 1px dotted var(--sklearn-color-border-box);\n",
+       "  border-radius: 0.25em;\n",
+       "  box-sizing: border-box;\n",
+       "  margin-bottom: 0.5em;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-estimator.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "/* on hover */\n",
+       "#sk-container-id-1 div.sk-estimator:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-estimator.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
+       "\n",
+       "/* Common style for \"i\" and \"?\" */\n",
+       "\n",
+       ".sk-estimator-doc-link,\n",
+       "a:link.sk-estimator-doc-link,\n",
+       "a:visited.sk-estimator-doc-link {\n",
+       "  float: right;\n",
+       "  font-size: smaller;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  border-radius: 1em;\n",
+       "  height: 1em;\n",
+       "  width: 1em;\n",
+       "  text-decoration: none !important;\n",
+       "  margin-left: 0.5em;\n",
+       "  text-align: center;\n",
+       "  /* unfitted */\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted,\n",
+       "a:link.sk-estimator-doc-link.fitted,\n",
+       "a:visited.sk-estimator-doc-link.fitted {\n",
+       "  /* fitted */\n",
+       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-1);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "/* Span, style for the box shown on hovering the info icon */\n",
+       ".sk-estimator-doc-link span {\n",
+       "  display: none;\n",
+       "  z-index: 9999;\n",
+       "  position: relative;\n",
+       "  font-weight: normal;\n",
+       "  right: .2ex;\n",
+       "  padding: .5ex;\n",
+       "  margin: .5ex;\n",
+       "  width: min-content;\n",
+       "  min-width: 20ex;\n",
+       "  max-width: 50ex;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  box-shadow: 2pt 2pt 4pt #999;\n",
+       "  /* unfitted */\n",
+       "  background: var(--sklearn-color-unfitted-level-0);\n",
+       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted span {\n",
+       "  /* fitted */\n",
+       "  background: var(--sklearn-color-fitted-level-0);\n",
+       "  border: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link:hover span {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
+       "\n",
+       "#sk-container-id-1 a.estimator_doc_link {\n",
+       "  float: right;\n",
+       "  font-size: 1rem;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  border-radius: 1rem;\n",
+       "  height: 1rem;\n",
+       "  width: 1rem;\n",
+       "  text-decoration: none;\n",
+       "  /* unfitted */\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 a.estimator_doc_link.fitted {\n",
+       "  /* fitted */\n",
+       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-1);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "#sk-container-id-1 a.estimator_doc_link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 a.estimator_doc_link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".estimator-table summary {\n",
+       "    padding: .5rem;\n",
+       "    font-family: monospace;\n",
+       "    cursor: pointer;\n",
+       "}\n",
+       "\n",
+       ".estimator-table details[open] {\n",
+       "    padding-left: 0.1rem;\n",
+       "    padding-right: 0.1rem;\n",
+       "    padding-bottom: 0.3rem;\n",
+       "}\n",
+       "\n",
+       ".estimator-table .parameters-table {\n",
+       "    margin-left: auto !important;\n",
+       "    margin-right: auto !important;\n",
+       "}\n",
+       "\n",
+       ".estimator-table .parameters-table tr:nth-child(odd) {\n",
+       "    background-color: #fff;\n",
+       "}\n",
+       "\n",
+       ".estimator-table .parameters-table tr:nth-child(even) {\n",
+       "    background-color: #f6f6f6;\n",
+       "}\n",
+       "\n",
+       ".estimator-table .parameters-table tr:hover {\n",
+       "    background-color: #e0e0e0;\n",
+       "}\n",
+       "\n",
+       ".estimator-table table td {\n",
+       "    border: 1px solid rgba(106, 105, 104, 0.232);\n",
+       "}\n",
+       "\n",
+       ".user-set td {\n",
+       "    color:rgb(255, 94, 0);\n",
+       "    text-align: left;\n",
+       "}\n",
+       "\n",
+       ".user-set td.value pre {\n",
+       "    color:rgb(255, 94, 0) !important;\n",
+       "    background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".default td {\n",
+       "    color: black;\n",
+       "    text-align: left;\n",
+       "}\n",
+       "\n",
+       ".user-set td i,\n",
+       ".default td i {\n",
+       "    color: black;\n",
+       "}\n",
+       "\n",
+       ".copy-paste-icon {\n",
+       "    background-image: url(data:image/svg+xml;base64,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);\n",
+       "    background-repeat: no-repeat;\n",
+       "    background-size: 14px 14px;\n",
+       "    background-position: 0;\n",
+       "    display: inline-block;\n",
+       "    width: 14px;\n",
+       "    height: 14px;\n",
+       "    cursor: pointer;\n",
+       "}\n",
+       "</style><body><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>GridSearchCV(cv=10, estimator=KNeighborsClassifier(),\n",
+       "             param_grid={&#x27;n_neighbors&#x27;: range(1, 51)})</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" ><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow\"><div><div>GridSearchCV</div></div><div><a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.7/modules/generated/sklearn.model_selection.GridSearchCV.html\">?<span>Documentation for GridSearchCV</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></div></label><div class=\"sk-toggleable__content fitted\" data-param-prefix=\"\">\n",
+       "        <div class=\"estimator-table\">\n",
+       "            <details>\n",
+       "                <summary>Parameters</summary>\n",
+       "                <table class=\"parameters-table\">\n",
+       "                  <tbody>\n",
+       "                    \n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('estimator',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">estimator&nbsp;</td>\n",
+       "            <td class=\"value\">KNeighborsClassifier()</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('param_grid',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">param_grid&nbsp;</td>\n",
+       "            <td class=\"value\">{&#x27;n_neighbors&#x27;: range(1, 51)}</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('scoring',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">scoring&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('n_jobs',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">n_jobs&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('refit',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">refit&nbsp;</td>\n",
+       "            <td class=\"value\">True</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('cv',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">cv&nbsp;</td>\n",
+       "            <td class=\"value\">10</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('verbose',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">verbose&nbsp;</td>\n",
+       "            <td class=\"value\">0</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('pre_dispatch',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">pre_dispatch&nbsp;</td>\n",
+       "            <td class=\"value\">&#x27;2*n_jobs&#x27;</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('error_score',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">error_score&nbsp;</td>\n",
+       "            <td class=\"value\">nan</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('return_train_score',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">return_train_score&nbsp;</td>\n",
+       "            <td class=\"value\">False</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "                  </tbody>\n",
+       "                </table>\n",
+       "            </details>\n",
+       "        </div>\n",
+       "    </div></div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" ><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow\"><div><div>best_estimator_: KNeighborsClassifier</div></div></label><div class=\"sk-toggleable__content fitted\" data-param-prefix=\"best_estimator___\"><pre>KNeighborsClassifier(n_neighbors=7)</pre></div></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-3\" type=\"checkbox\" ><label for=\"sk-estimator-id-3\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow\"><div><div>KNeighborsClassifier</div></div><div><a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.7/modules/generated/sklearn.neighbors.KNeighborsClassifier.html\">?<span>Documentation for KNeighborsClassifier</span></a></div></label><div class=\"sk-toggleable__content fitted\" data-param-prefix=\"best_estimator___\">\n",
+       "        <div class=\"estimator-table\">\n",
+       "            <details>\n",
+       "                <summary>Parameters</summary>\n",
+       "                <table class=\"parameters-table\">\n",
+       "                  <tbody>\n",
+       "                    \n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('n_neighbors',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">n_neighbors&nbsp;</td>\n",
+       "            <td class=\"value\">7</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('weights',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">weights&nbsp;</td>\n",
+       "            <td class=\"value\">&#x27;uniform&#x27;</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('algorithm',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">algorithm&nbsp;</td>\n",
+       "            <td class=\"value\">&#x27;auto&#x27;</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('leaf_size',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">leaf_size&nbsp;</td>\n",
+       "            <td class=\"value\">30</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('p',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">p&nbsp;</td>\n",
+       "            <td class=\"value\">2</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('metric',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">metric&nbsp;</td>\n",
+       "            <td class=\"value\">&#x27;minkowski&#x27;</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('metric_params',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">metric_params&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('n_jobs',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">n_jobs&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "                  </tbody>\n",
+       "                </table>\n",
+       "            </details>\n",
+       "        </div>\n",
+       "    </div></div></div></div></div></div></div></div></div></div><script>function copyToClipboard(text, element) {\n",
+       "    // Get the parameter prefix from the closest toggleable content\n",
+       "    const toggleableContent = element.closest('.sk-toggleable__content');\n",
+       "    const paramPrefix = toggleableContent ? toggleableContent.dataset.paramPrefix : '';\n",
+       "    const fullParamName = paramPrefix ? `${paramPrefix}${text}` : text;\n",
+       "\n",
+       "    const originalStyle = element.style;\n",
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+       "\n",
+       "    navigator.clipboard.writeText(fullParamName)\n",
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+       "\n",
+       "    element.setAttribute('title', fullParamName);\n",
+       "});\n",
+       "</script></body>"
+      ],
+      "text/plain": [
+       "GridSearchCV(cv=10, estimator=KNeighborsClassifier(),\n",
+       "             param_grid={'n_neighbors': range(1, 51)})"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Fit the grid search cross-validation on the X (standardized predictors) and y (predicted wine class) training data\n",
+    "wine_tune_grid.fit(X_train, y_train)\n",
+    "\n",
+    " "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "7f33adf6",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+       "      <th></th>\n",
+       "      <th>mean_fit_time</th>\n",
+       "      <th>std_fit_time</th>\n",
+       "      <th>mean_score_time</th>\n",
+       "      <th>std_score_time</th>\n",
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+       "      <th>split1_test_score</th>\n",
+       "      <th>split2_test_score</th>\n",
+       "      <th>split3_test_score</th>\n",
+       "      <th>split4_test_score</th>\n",
+       "      <th>split5_test_score</th>\n",
+       "      <th>split6_test_score</th>\n",
+       "      <th>split7_test_score</th>\n",
+       "      <th>split8_test_score</th>\n",
+       "      <th>split9_test_score</th>\n",
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+       "      <td>39</td>\n",
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+       "      <td>0.001786</td>\n",
+       "      <td>0.000405</td>\n",
+       "      <td>0.003006</td>\n",
+       "      <td>0.000464</td>\n",
+       "      <td>2</td>\n",
+       "      <td>{'n_neighbors': 2}</td>\n",
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+       "      <td>0.089628</td>\n",
+       "      <td>50</td>\n",
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+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>0.001955</td>\n",
+       "      <td>0.000384</td>\n",
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+       "      <td>0.000406</td>\n",
+       "      <td>3</td>\n",
+       "      <td>{'n_neighbors': 3}</td>\n",
+       "      <td>1.000000</td>\n",
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+       "      <td>1.000000</td>\n",
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+       "      <td>0.051217</td>\n",
+       "      <td>28</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
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+       "      <td>{'n_neighbors': 5}</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.969780</td>\n",
+       "      <td>0.037042</td>\n",
+       "      <td>7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>0.002122</td>\n",
+       "      <td>0.000373</td>\n",
+       "      <td>0.002833</td>\n",
+       "      <td>0.000349</td>\n",
+       "      <td>6</td>\n",
+       "      <td>{'n_neighbors': 6}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.969780</td>\n",
+       "      <td>0.037042</td>\n",
+       "      <td>7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>0.002104</td>\n",
+       "      <td>0.000284</td>\n",
+       "      <td>0.003184</td>\n",
+       "      <td>0.000442</td>\n",
+       "      <td>7</td>\n",
+       "      <td>{'n_neighbors': 7}</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.977473</td>\n",
+       "      <td>0.034441</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>0.002055</td>\n",
+       "      <td>0.000344</td>\n",
+       "      <td>0.003083</td>\n",
+       "      <td>0.000392</td>\n",
+       "      <td>8</td>\n",
+       "      <td>{'n_neighbors': 8}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.846154</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.954396</td>\n",
+       "      <td>0.050719</td>\n",
+       "      <td>39</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>0.001983</td>\n",
+       "      <td>0.000167</td>\n",
+       "      <td>0.003221</td>\n",
+       "      <td>0.000321</td>\n",
+       "      <td>9</td>\n",
+       "      <td>{'n_neighbors': 9}</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.969780</td>\n",
+       "      <td>0.037042</td>\n",
+       "      <td>9</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>0.002034</td>\n",
+       "      <td>0.000397</td>\n",
+       "      <td>0.003299</td>\n",
+       "      <td>0.000369</td>\n",
+       "      <td>10</td>\n",
+       "      <td>{'n_neighbors': 10}</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.846154</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.954396</td>\n",
+       "      <td>0.050719</td>\n",
+       "      <td>39</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>0.002030</td>\n",
+       "      <td>0.000517</td>\n",
+       "      <td>0.003216</td>\n",
+       "      <td>0.000700</td>\n",
+       "      <td>11</td>\n",
+       "      <td>{'n_neighbors': 11}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.962637</td>\n",
+       "      <td>0.037411</td>\n",
+       "      <td>17</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>0.001835</td>\n",
+       "      <td>0.000428</td>\n",
+       "      <td>0.002765</td>\n",
+       "      <td>0.000398</td>\n",
+       "      <td>12</td>\n",
+       "      <td>{'n_neighbors': 12}</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.969780</td>\n",
+       "      <td>0.037042</td>\n",
+       "      <td>9</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>0.002262</td>\n",
+       "      <td>0.000414</td>\n",
+       "      <td>0.003020</td>\n",
+       "      <td>0.000175</td>\n",
+       "      <td>13</td>\n",
+       "      <td>{'n_neighbors': 13}</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.977473</td>\n",
+       "      <td>0.034441</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>0.002057</td>\n",
+       "      <td>0.000080</td>\n",
+       "      <td>0.003090</td>\n",
+       "      <td>0.000367</td>\n",
+       "      <td>14</td>\n",
+       "      <td>{'n_neighbors': 14}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.962637</td>\n",
+       "      <td>0.037411</td>\n",
+       "      <td>17</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>0.002085</td>\n",
+       "      <td>0.000276</td>\n",
+       "      <td>0.003104</td>\n",
+       "      <td>0.000370</td>\n",
+       "      <td>15</td>\n",
+       "      <td>{'n_neighbors': 15}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.962637</td>\n",
+       "      <td>0.037411</td>\n",
+       "      <td>17</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>0.002043</td>\n",
+       "      <td>0.000083</td>\n",
+       "      <td>0.002839</td>\n",
+       "      <td>0.000472</td>\n",
+       "      <td>16</td>\n",
+       "      <td>{'n_neighbors': 16}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.962637</td>\n",
+       "      <td>0.037411</td>\n",
+       "      <td>17</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>0.002071</td>\n",
+       "      <td>0.000461</td>\n",
+       "      <td>0.002936</td>\n",
+       "      <td>0.000430</td>\n",
+       "      <td>17</td>\n",
+       "      <td>{'n_neighbors': 17}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.962637</td>\n",
+       "      <td>0.037411</td>\n",
+       "      <td>17</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>0.002201</td>\n",
+       "      <td>0.000489</td>\n",
+       "      <td>0.003014</td>\n",
+       "      <td>0.000580</td>\n",
+       "      <td>18</td>\n",
+       "      <td>{'n_neighbors': 18}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.962637</td>\n",
+       "      <td>0.037411</td>\n",
+       "      <td>17</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>0.002035</td>\n",
+       "      <td>0.000086</td>\n",
+       "      <td>0.003053</td>\n",
+       "      <td>0.000311</td>\n",
+       "      <td>19</td>\n",
+       "      <td>{'n_neighbors': 19}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.962637</td>\n",
+       "      <td>0.037411</td>\n",
+       "      <td>17</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>0.001978</td>\n",
+       "      <td>0.000142</td>\n",
+       "      <td>0.002812</td>\n",
+       "      <td>0.000435</td>\n",
+       "      <td>20</td>\n",
+       "      <td>{'n_neighbors': 20}</td>\n",
+       "      <td>0.857143</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.963187</td>\n",
+       "      <td>0.048777</td>\n",
+       "      <td>11</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>0.002009</td>\n",
+       "      <td>0.000400</td>\n",
+       "      <td>0.003075</td>\n",
+       "      <td>0.000414</td>\n",
+       "      <td>21</td>\n",
+       "      <td>{'n_neighbors': 21}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.970330</td>\n",
+       "      <td>0.036380</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>0.002261</td>\n",
+       "      <td>0.000367</td>\n",
+       "      <td>0.003033</td>\n",
+       "      <td>0.000399</td>\n",
+       "      <td>22</td>\n",
+       "      <td>{'n_neighbors': 22}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.970330</td>\n",
+       "      <td>0.036380</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>0.002300</td>\n",
+       "      <td>0.000326</td>\n",
+       "      <td>0.002978</td>\n",
+       "      <td>0.000085</td>\n",
+       "      <td>23</td>\n",
+       "      <td>{'n_neighbors': 23}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.962637</td>\n",
+       "      <td>0.037411</td>\n",
+       "      <td>13</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>0.002111</td>\n",
+       "      <td>0.000169</td>\n",
+       "      <td>0.003144</td>\n",
+       "      <td>0.000445</td>\n",
+       "      <td>24</td>\n",
+       "      <td>{'n_neighbors': 24}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.970330</td>\n",
+       "      <td>0.036380</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>0.002140</td>\n",
+       "      <td>0.000519</td>\n",
+       "      <td>0.003224</td>\n",
+       "      <td>0.000382</td>\n",
+       "      <td>25</td>\n",
+       "      <td>{'n_neighbors': 25}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.846154</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.954945</td>\n",
+       "      <td>0.050406</td>\n",
+       "      <td>33</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>0.002215</td>\n",
+       "      <td>0.000317</td>\n",
+       "      <td>0.002897</td>\n",
+       "      <td>0.000187</td>\n",
+       "      <td>26</td>\n",
+       "      <td>{'n_neighbors': 26}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.846154</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.962637</td>\n",
+       "      <td>0.050823</td>\n",
+       "      <td>13</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>0.002096</td>\n",
+       "      <td>0.000359</td>\n",
+       "      <td>0.003045</td>\n",
+       "      <td>0.000297</td>\n",
+       "      <td>27</td>\n",
+       "      <td>{'n_neighbors': 27}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.846154</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.954945</td>\n",
+       "      <td>0.050406</td>\n",
+       "      <td>33</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>0.001970</td>\n",
+       "      <td>0.000243</td>\n",
+       "      <td>0.002825</td>\n",
+       "      <td>0.000545</td>\n",
+       "      <td>28</td>\n",
+       "      <td>{'n_neighbors': 28}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.962637</td>\n",
+       "      <td>0.037411</td>\n",
+       "      <td>13</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>0.002123</td>\n",
+       "      <td>0.000372</td>\n",
+       "      <td>0.002904</td>\n",
+       "      <td>0.000392</td>\n",
+       "      <td>29</td>\n",
+       "      <td>{'n_neighbors': 29}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.962637</td>\n",
+       "      <td>0.037411</td>\n",
+       "      <td>13</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>0.002182</td>\n",
+       "      <td>0.000272</td>\n",
+       "      <td>0.003167</td>\n",
+       "      <td>0.000174</td>\n",
+       "      <td>30</td>\n",
+       "      <td>{'n_neighbors': 30}</td>\n",
+       "      <td>0.857143</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.947802</td>\n",
+       "      <td>0.046832</td>\n",
+       "      <td>42</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30</th>\n",
+       "      <td>0.002125</td>\n",
+       "      <td>0.000473</td>\n",
+       "      <td>0.002778</td>\n",
+       "      <td>0.000469</td>\n",
+       "      <td>31</td>\n",
+       "      <td>{'n_neighbors': 31}</td>\n",
+       "      <td>0.857143</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.955495</td>\n",
+       "      <td>0.048430</td>\n",
+       "      <td>29</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>31</th>\n",
+       "      <td>0.002096</td>\n",
+       "      <td>0.000485</td>\n",
+       "      <td>0.002906</td>\n",
+       "      <td>0.000275</td>\n",
+       "      <td>32</td>\n",
+       "      <td>{'n_neighbors': 32}</td>\n",
+       "      <td>0.857143</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.955495</td>\n",
+       "      <td>0.048430</td>\n",
+       "      <td>29</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>0.002165</td>\n",
+       "      <td>0.000218</td>\n",
+       "      <td>0.002834</td>\n",
+       "      <td>0.000393</td>\n",
+       "      <td>33</td>\n",
+       "      <td>{'n_neighbors': 33}</td>\n",
+       "      <td>0.857143</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.955495</td>\n",
+       "      <td>0.048430</td>\n",
+       "      <td>29</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>33</th>\n",
+       "      <td>0.001930</td>\n",
+       "      <td>0.000154</td>\n",
+       "      <td>0.002948</td>\n",
+       "      <td>0.000218</td>\n",
+       "      <td>34</td>\n",
+       "      <td>{'n_neighbors': 34}</td>\n",
+       "      <td>0.857143</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.963187</td>\n",
+       "      <td>0.048777</td>\n",
+       "      <td>11</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>34</th>\n",
+       "      <td>0.002257</td>\n",
+       "      <td>0.000424</td>\n",
+       "      <td>0.003071</td>\n",
+       "      <td>0.000257</td>\n",
+       "      <td>35</td>\n",
+       "      <td>{'n_neighbors': 35}</td>\n",
+       "      <td>0.857143</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.955495</td>\n",
+       "      <td>0.048430</td>\n",
+       "      <td>29</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>35</th>\n",
+       "      <td>0.002071</td>\n",
+       "      <td>0.000167</td>\n",
+       "      <td>0.002812</td>\n",
+       "      <td>0.000356</td>\n",
+       "      <td>36</td>\n",
+       "      <td>{'n_neighbors': 36}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.962637</td>\n",
+       "      <td>0.037411</td>\n",
+       "      <td>17</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>36</th>\n",
+       "      <td>0.001962</td>\n",
+       "      <td>0.000575</td>\n",
+       "      <td>0.002976</td>\n",
+       "      <td>0.000531</td>\n",
+       "      <td>37</td>\n",
+       "      <td>{'n_neighbors': 37}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.962637</td>\n",
+       "      <td>0.037411</td>\n",
+       "      <td>17</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>37</th>\n",
+       "      <td>0.002059</td>\n",
+       "      <td>0.000344</td>\n",
+       "      <td>0.002983</td>\n",
+       "      <td>0.000384</td>\n",
+       "      <td>38</td>\n",
+       "      <td>{'n_neighbors': 38}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.962637</td>\n",
+       "      <td>0.037411</td>\n",
+       "      <td>17</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>38</th>\n",
+       "      <td>0.002038</td>\n",
+       "      <td>0.000085</td>\n",
+       "      <td>0.003046</td>\n",
+       "      <td>0.000451</td>\n",
+       "      <td>39</td>\n",
+       "      <td>{'n_neighbors': 39}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.962637</td>\n",
+       "      <td>0.037411</td>\n",
+       "      <td>17</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>39</th>\n",
+       "      <td>0.002156</td>\n",
+       "      <td>0.000544</td>\n",
+       "      <td>0.003078</td>\n",
+       "      <td>0.000457</td>\n",
+       "      <td>40</td>\n",
+       "      <td>{'n_neighbors': 40}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.954945</td>\n",
+       "      <td>0.036842</td>\n",
+       "      <td>35</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>40</th>\n",
+       "      <td>0.002072</td>\n",
+       "      <td>0.000309</td>\n",
+       "      <td>0.003116</td>\n",
+       "      <td>0.000515</td>\n",
+       "      <td>41</td>\n",
+       "      <td>{'n_neighbors': 41}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.970330</td>\n",
+       "      <td>0.036380</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>41</th>\n",
+       "      <td>0.002147</td>\n",
+       "      <td>0.000454</td>\n",
+       "      <td>0.003060</td>\n",
+       "      <td>0.000233</td>\n",
+       "      <td>42</td>\n",
+       "      <td>{'n_neighbors': 42}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.954945</td>\n",
+       "      <td>0.036842</td>\n",
+       "      <td>35</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>42</th>\n",
+       "      <td>0.002306</td>\n",
+       "      <td>0.000392</td>\n",
+       "      <td>0.003145</td>\n",
+       "      <td>0.000430</td>\n",
+       "      <td>43</td>\n",
+       "      <td>{'n_neighbors': 43}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.954945</td>\n",
+       "      <td>0.036842</td>\n",
+       "      <td>35</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>43</th>\n",
+       "      <td>0.002034</td>\n",
+       "      <td>0.000224</td>\n",
+       "      <td>0.003070</td>\n",
+       "      <td>0.000529</td>\n",
+       "      <td>44</td>\n",
+       "      <td>{'n_neighbors': 44}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.846154</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.947253</td>\n",
+       "      <td>0.048787</td>\n",
+       "      <td>44</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>44</th>\n",
+       "      <td>0.002102</td>\n",
+       "      <td>0.000401</td>\n",
+       "      <td>0.003192</td>\n",
+       "      <td>0.000408</td>\n",
+       "      <td>45</td>\n",
+       "      <td>{'n_neighbors': 45}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.846154</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.947253</td>\n",
+       "      <td>0.048787</td>\n",
+       "      <td>44</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>45</th>\n",
+       "      <td>0.002042</td>\n",
+       "      <td>0.000299</td>\n",
+       "      <td>0.002879</td>\n",
+       "      <td>0.000358</td>\n",
+       "      <td>46</td>\n",
+       "      <td>{'n_neighbors': 46}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.846154</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.947253</td>\n",
+       "      <td>0.048787</td>\n",
+       "      <td>44</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>46</th>\n",
+       "      <td>0.001945</td>\n",
+       "      <td>0.000383</td>\n",
+       "      <td>0.002961</td>\n",
+       "      <td>0.000453</td>\n",
+       "      <td>47</td>\n",
+       "      <td>{'n_neighbors': 47}</td>\n",
+       "      <td>0.857143</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.947802</td>\n",
+       "      <td>0.046832</td>\n",
+       "      <td>42</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>47</th>\n",
+       "      <td>0.002023</td>\n",
+       "      <td>0.000381</td>\n",
+       "      <td>0.002955</td>\n",
+       "      <td>0.000451</td>\n",
+       "      <td>48</td>\n",
+       "      <td>{'n_neighbors': 48}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.947253</td>\n",
+       "      <td>0.034594</td>\n",
+       "      <td>44</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>0.002224</td>\n",
+       "      <td>0.000456</td>\n",
+       "      <td>0.002939</td>\n",
+       "      <td>0.000459</td>\n",
+       "      <td>49</td>\n",
+       "      <td>{'n_neighbors': 49}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.947253</td>\n",
+       "      <td>0.034594</td>\n",
+       "      <td>44</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>0.002074</td>\n",
+       "      <td>0.000364</td>\n",
+       "      <td>0.003102</td>\n",
+       "      <td>0.000163</td>\n",
+       "      <td>50</td>\n",
+       "      <td>{'n_neighbors': 50}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.947253</td>\n",
+       "      <td>0.034594</td>\n",
+       "      <td>44</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    mean_fit_time  std_fit_time  mean_score_time  std_score_time  \\\n",
+       "0        0.002199      0.000510         0.003247        0.000509   \n",
+       "1        0.001786      0.000405         0.003006        0.000464   \n",
+       "2        0.001955      0.000384         0.002786        0.000406   \n",
+       "3        0.002489      0.000418         0.002739        0.000585   \n",
+       "4        0.002197      0.000430         0.002916        0.000301   \n",
+       "5        0.002122      0.000373         0.002833        0.000349   \n",
+       "6        0.002104      0.000284         0.003184        0.000442   \n",
+       "7        0.002055      0.000344         0.003083        0.000392   \n",
+       "8        0.001983      0.000167         0.003221        0.000321   \n",
+       "9        0.002034      0.000397         0.003299        0.000369   \n",
+       "10       0.002030      0.000517         0.003216        0.000700   \n",
+       "11       0.001835      0.000428         0.002765        0.000398   \n",
+       "12       0.002262      0.000414         0.003020        0.000175   \n",
+       "13       0.002057      0.000080         0.003090        0.000367   \n",
+       "14       0.002085      0.000276         0.003104        0.000370   \n",
+       "15       0.002043      0.000083         0.002839        0.000472   \n",
+       "16       0.002071      0.000461         0.002936        0.000430   \n",
+       "17       0.002201      0.000489         0.003014        0.000580   \n",
+       "18       0.002035      0.000086         0.003053        0.000311   \n",
+       "19       0.001978      0.000142         0.002812        0.000435   \n",
+       "20       0.002009      0.000400         0.003075        0.000414   \n",
+       "21       0.002261      0.000367         0.003033        0.000399   \n",
+       "22       0.002300      0.000326         0.002978        0.000085   \n",
+       "23       0.002111      0.000169         0.003144        0.000445   \n",
+       "24       0.002140      0.000519         0.003224        0.000382   \n",
+       "25       0.002215      0.000317         0.002897        0.000187   \n",
+       "26       0.002096      0.000359         0.003045        0.000297   \n",
+       "27       0.001970      0.000243         0.002825        0.000545   \n",
+       "28       0.002123      0.000372         0.002904        0.000392   \n",
+       "29       0.002182      0.000272         0.003167        0.000174   \n",
+       "30       0.002125      0.000473         0.002778        0.000469   \n",
+       "31       0.002096      0.000485         0.002906        0.000275   \n",
+       "32       0.002165      0.000218         0.002834        0.000393   \n",
+       "33       0.001930      0.000154         0.002948        0.000218   \n",
+       "34       0.002257      0.000424         0.003071        0.000257   \n",
+       "35       0.002071      0.000167         0.002812        0.000356   \n",
+       "36       0.001962      0.000575         0.002976        0.000531   \n",
+       "37       0.002059      0.000344         0.002983        0.000384   \n",
+       "38       0.002038      0.000085         0.003046        0.000451   \n",
+       "39       0.002156      0.000544         0.003078        0.000457   \n",
+       "40       0.002072      0.000309         0.003116        0.000515   \n",
+       "41       0.002147      0.000454         0.003060        0.000233   \n",
+       "42       0.002306      0.000392         0.003145        0.000430   \n",
+       "43       0.002034      0.000224         0.003070        0.000529   \n",
+       "44       0.002102      0.000401         0.003192        0.000408   \n",
+       "45       0.002042      0.000299         0.002879        0.000358   \n",
+       "46       0.001945      0.000383         0.002961        0.000453   \n",
+       "47       0.002023      0.000381         0.002955        0.000451   \n",
+       "48       0.002224      0.000456         0.002939        0.000459   \n",
+       "49       0.002074      0.000364         0.003102        0.000163   \n",
+       "\n",
+       "    param_n_neighbors               params  split0_test_score  \\\n",
+       "0                   1   {'n_neighbors': 1}           1.000000   \n",
+       "1                   2   {'n_neighbors': 2}           1.000000   \n",
+       "2                   3   {'n_neighbors': 3}           1.000000   \n",
+       "3                   4   {'n_neighbors': 4}           0.928571   \n",
+       "4                   5   {'n_neighbors': 5}           1.000000   \n",
+       "5                   6   {'n_neighbors': 6}           0.928571   \n",
+       "6                   7   {'n_neighbors': 7}           1.000000   \n",
+       "7                   8   {'n_neighbors': 8}           0.928571   \n",
+       "8                   9   {'n_neighbors': 9}           1.000000   \n",
+       "9                  10  {'n_neighbors': 10}           1.000000   \n",
+       "10                 11  {'n_neighbors': 11}           0.928571   \n",
+       "11                 12  {'n_neighbors': 12}           1.000000   \n",
+       "12                 13  {'n_neighbors': 13}           1.000000   \n",
+       "13                 14  {'n_neighbors': 14}           0.928571   \n",
+       "14                 15  {'n_neighbors': 15}           0.928571   \n",
+       "15                 16  {'n_neighbors': 16}           0.928571   \n",
+       "16                 17  {'n_neighbors': 17}           0.928571   \n",
+       "17                 18  {'n_neighbors': 18}           0.928571   \n",
+       "18                 19  {'n_neighbors': 19}           0.928571   \n",
+       "19                 20  {'n_neighbors': 20}           0.857143   \n",
+       "20                 21  {'n_neighbors': 21}           0.928571   \n",
+       "21                 22  {'n_neighbors': 22}           0.928571   \n",
+       "22                 23  {'n_neighbors': 23}           0.928571   \n",
+       "23                 24  {'n_neighbors': 24}           0.928571   \n",
+       "24                 25  {'n_neighbors': 25}           0.928571   \n",
+       "25                 26  {'n_neighbors': 26}           0.928571   \n",
+       "26                 27  {'n_neighbors': 27}           0.928571   \n",
+       "27                 28  {'n_neighbors': 28}           0.928571   \n",
+       "28                 29  {'n_neighbors': 29}           0.928571   \n",
+       "29                 30  {'n_neighbors': 30}           0.857143   \n",
+       "30                 31  {'n_neighbors': 31}           0.857143   \n",
+       "31                 32  {'n_neighbors': 32}           0.857143   \n",
+       "32                 33  {'n_neighbors': 33}           0.857143   \n",
+       "33                 34  {'n_neighbors': 34}           0.857143   \n",
+       "34                 35  {'n_neighbors': 35}           0.857143   \n",
+       "35                 36  {'n_neighbors': 36}           0.928571   \n",
+       "36                 37  {'n_neighbors': 37}           0.928571   \n",
+       "37                 38  {'n_neighbors': 38}           0.928571   \n",
+       "38                 39  {'n_neighbors': 39}           0.928571   \n",
+       "39                 40  {'n_neighbors': 40}           0.928571   \n",
+       "40                 41  {'n_neighbors': 41}           0.928571   \n",
+       "41                 42  {'n_neighbors': 42}           0.928571   \n",
+       "42                 43  {'n_neighbors': 43}           0.928571   \n",
+       "43                 44  {'n_neighbors': 44}           0.928571   \n",
+       "44                 45  {'n_neighbors': 45}           0.928571   \n",
+       "45                 46  {'n_neighbors': 46}           0.928571   \n",
+       "46                 47  {'n_neighbors': 47}           0.857143   \n",
+       "47                 48  {'n_neighbors': 48}           0.928571   \n",
+       "48                 49  {'n_neighbors': 49}           0.928571   \n",
+       "49                 50  {'n_neighbors': 50}           0.928571   \n",
+       "\n",
+       "    split1_test_score  split2_test_score  split3_test_score  \\\n",
+       "0            0.928571                1.0           0.692308   \n",
+       "1            0.928571                1.0           0.692308   \n",
+       "2            0.928571                1.0           0.846154   \n",
+       "3            0.928571                1.0           0.846154   \n",
+       "4            0.928571                1.0           0.923077   \n",
+       "5            1.000000                1.0           0.923077   \n",
+       "6            0.928571                1.0           0.923077   \n",
+       "7            1.000000                1.0           0.846154   \n",
+       "8            0.928571                1.0           0.923077   \n",
+       "9            0.928571                1.0           0.846154   \n",
+       "10           0.928571                1.0           0.923077   \n",
+       "11           0.928571                1.0           0.923077   \n",
+       "12           0.928571                1.0           1.000000   \n",
+       "13           0.928571                1.0           0.923077   \n",
+       "14           0.928571                1.0           0.923077   \n",
+       "15           0.928571                1.0           0.923077   \n",
+       "16           0.928571                1.0           0.923077   \n",
+       "17           0.928571                1.0           0.923077   \n",
+       "18           0.928571                1.0           0.923077   \n",
+       "19           0.928571                1.0           0.923077   \n",
+       "20           0.928571                1.0           0.923077   \n",
+       "21           0.928571                1.0           0.923077   \n",
+       "22           0.928571                1.0           0.923077   \n",
+       "23           0.928571                1.0           0.923077   \n",
+       "24           0.928571                1.0           0.846154   \n",
+       "25           0.928571                1.0           0.846154   \n",
+       "26           0.928571                1.0           0.846154   \n",
+       "27           0.928571                1.0           0.923077   \n",
+       "28           0.928571                1.0           0.923077   \n",
+       "29           0.928571                1.0           0.923077   \n",
+       "30           0.928571                1.0           0.923077   \n",
+       "31           0.928571                1.0           0.923077   \n",
+       "32           0.928571                1.0           0.923077   \n",
+       "33           0.928571                1.0           0.923077   \n",
+       "34           0.928571                1.0           0.923077   \n",
+       "35           0.928571                1.0           0.923077   \n",
+       "36           0.928571                1.0           0.923077   \n",
+       "37           0.928571                1.0           0.923077   \n",
+       "38           0.928571                1.0           0.923077   \n",
+       "39           0.928571                1.0           0.923077   \n",
+       "40           0.928571                1.0           1.000000   \n",
+       "41           0.928571                1.0           0.923077   \n",
+       "42           0.928571                1.0           0.923077   \n",
+       "43           0.928571                1.0           0.846154   \n",
+       "44           0.928571                1.0           0.846154   \n",
+       "45           0.928571                1.0           0.846154   \n",
+       "46           0.928571                1.0           0.923077   \n",
+       "47           0.928571                1.0           0.923077   \n",
+       "48           0.928571                1.0           0.923077   \n",
+       "49           0.928571                1.0           0.923077   \n",
+       "\n",
+       "    split4_test_score  split5_test_score  split6_test_score  \\\n",
+       "0            1.000000                1.0           1.000000   \n",
+       "1            1.000000                1.0           1.000000   \n",
+       "2            1.000000                1.0           1.000000   \n",
+       "3            0.923077                1.0           1.000000   \n",
+       "4            0.923077                1.0           1.000000   \n",
+       "5            0.923077                1.0           1.000000   \n",
+       "6            0.923077                1.0           1.000000   \n",
+       "7            0.923077                1.0           1.000000   \n",
+       "8            0.923077                1.0           1.000000   \n",
+       "9            0.923077                1.0           0.923077   \n",
+       "10           0.923077                1.0           1.000000   \n",
+       "11           0.923077                1.0           1.000000   \n",
+       "12           0.923077                1.0           1.000000   \n",
+       "13           0.923077                1.0           1.000000   \n",
+       "14           0.923077                1.0           1.000000   \n",
+       "15           0.923077                1.0           1.000000   \n",
+       "16           0.923077                1.0           1.000000   \n",
+       "17           0.923077                1.0           1.000000   \n",
+       "18           0.923077                1.0           1.000000   \n",
+       "19           0.923077                1.0           1.000000   \n",
+       "20           0.923077                1.0           1.000000   \n",
+       "21           0.923077                1.0           1.000000   \n",
+       "22           0.923077                1.0           1.000000   \n",
+       "23           0.923077                1.0           1.000000   \n",
+       "24           0.923077                1.0           1.000000   \n",
+       "25           0.923077                1.0           1.000000   \n",
+       "26           0.923077                1.0           1.000000   \n",
+       "27           0.923077                1.0           1.000000   \n",
+       "28           0.923077                1.0           1.000000   \n",
+       "29           0.923077                1.0           1.000000   \n",
+       "30           0.923077                1.0           1.000000   \n",
+       "31           0.923077                1.0           1.000000   \n",
+       "32           0.923077                1.0           1.000000   \n",
+       "33           0.923077                1.0           1.000000   \n",
+       "34           0.923077                1.0           0.923077   \n",
+       "35           0.923077                1.0           1.000000   \n",
+       "36           0.923077                1.0           1.000000   \n",
+       "37           0.923077                1.0           1.000000   \n",
+       "38           0.923077                1.0           1.000000   \n",
+       "39           0.923077                1.0           1.000000   \n",
+       "40           0.923077                1.0           1.000000   \n",
+       "41           0.923077                1.0           1.000000   \n",
+       "42           0.923077                1.0           1.000000   \n",
+       "43           0.923077                1.0           1.000000   \n",
+       "44           0.923077                1.0           1.000000   \n",
+       "45           0.923077                1.0           1.000000   \n",
+       "46           0.923077                1.0           1.000000   \n",
+       "47           0.923077                1.0           1.000000   \n",
+       "48           0.923077                1.0           1.000000   \n",
+       "49           0.923077                1.0           1.000000   \n",
+       "\n",
+       "    split7_test_score  split8_test_score  split9_test_score  mean_test_score  \\\n",
+       "0            1.000000           1.000000           0.923077         0.954396   \n",
+       "1            0.923077           0.923077           0.923077         0.939011   \n",
+       "2            1.000000           0.923077           0.923077         0.962088   \n",
+       "3            1.000000           0.923077           1.000000         0.954945   \n",
+       "4            1.000000           0.923077           1.000000         0.969780   \n",
+       "5            1.000000           0.923077           1.000000         0.969780   \n",
+       "6            1.000000           1.000000           1.000000         0.977473   \n",
+       "7            0.923077           0.923077           1.000000         0.954396   \n",
+       "8            0.923077           1.000000           1.000000         0.969780   \n",
+       "9            0.923077           1.000000           1.000000         0.954396   \n",
+       "10           0.923077           1.000000           1.000000         0.962637   \n",
+       "11           0.923077           1.000000           1.000000         0.969780   \n",
+       "12           0.923077           1.000000           1.000000         0.977473   \n",
+       "13           0.923077           1.000000           1.000000         0.962637   \n",
+       "14           0.923077           1.000000           1.000000         0.962637   \n",
+       "15           0.923077           1.000000           1.000000         0.962637   \n",
+       "16           0.923077           1.000000           1.000000         0.962637   \n",
+       "17           0.923077           1.000000           1.000000         0.962637   \n",
+       "18           0.923077           1.000000           1.000000         0.962637   \n",
+       "19           1.000000           1.000000           1.000000         0.963187   \n",
+       "20           1.000000           1.000000           1.000000         0.970330   \n",
+       "21           1.000000           1.000000           1.000000         0.970330   \n",
+       "22           1.000000           1.000000           0.923077         0.962637   \n",
+       "23           1.000000           1.000000           1.000000         0.970330   \n",
+       "24           1.000000           1.000000           0.923077         0.954945   \n",
+       "25           1.000000           1.000000           1.000000         0.962637   \n",
+       "26           1.000000           1.000000           0.923077         0.954945   \n",
+       "27           1.000000           1.000000           0.923077         0.962637   \n",
+       "28           1.000000           1.000000           0.923077         0.962637   \n",
+       "29           0.923077           1.000000           0.923077         0.947802   \n",
+       "30           1.000000           1.000000           0.923077         0.955495   \n",
+       "31           1.000000           1.000000           0.923077         0.955495   \n",
+       "32           1.000000           1.000000           0.923077         0.955495   \n",
+       "33           1.000000           1.000000           1.000000         0.963187   \n",
+       "34           1.000000           1.000000           1.000000         0.955495   \n",
+       "35           0.923077           1.000000           1.000000         0.962637   \n",
+       "36           0.923077           1.000000           1.000000         0.962637   \n",
+       "37           0.923077           1.000000           1.000000         0.962637   \n",
+       "38           0.923077           1.000000           1.000000         0.962637   \n",
+       "39           0.923077           1.000000           0.923077         0.954945   \n",
+       "40           0.923077           1.000000           1.000000         0.970330   \n",
+       "41           0.923077           1.000000           0.923077         0.954945   \n",
+       "42           0.923077           1.000000           0.923077         0.954945   \n",
+       "43           0.923077           1.000000           0.923077         0.947253   \n",
+       "44           0.923077           1.000000           0.923077         0.947253   \n",
+       "45           0.923077           1.000000           0.923077         0.947253   \n",
+       "46           0.923077           1.000000           0.923077         0.947802   \n",
+       "47           0.923077           0.923077           0.923077         0.947253   \n",
+       "48           0.923077           0.923077           0.923077         0.947253   \n",
+       "49           0.923077           0.923077           0.923077         0.947253   \n",
+       "\n",
+       "    std_test_score  rank_test_score  \n",
+       "0         0.092139               39  \n",
+       "1         0.089628               50  \n",
+       "2         0.051217               28  \n",
+       "3         0.050406               35  \n",
+       "4         0.037042                7  \n",
+       "5         0.037042                7  \n",
+       "6         0.034441                1  \n",
+       "7         0.050719               39  \n",
+       "8         0.037042                9  \n",
+       "9         0.050719               39  \n",
+       "10        0.037411               17  \n",
+       "11        0.037042                9  \n",
+       "12        0.034441                1  \n",
+       "13        0.037411               17  \n",
+       "14        0.037411               17  \n",
+       "15        0.037411               17  \n",
+       "16        0.037411               17  \n",
+       "17        0.037411               17  \n",
+       "18        0.037411               17  \n",
+       "19        0.048777               11  \n",
+       "20        0.036380                3  \n",
+       "21        0.036380                3  \n",
+       "22        0.037411               13  \n",
+       "23        0.036380                3  \n",
+       "24        0.050406               33  \n",
+       "25        0.050823               13  \n",
+       "26        0.050406               33  \n",
+       "27        0.037411               13  \n",
+       "28        0.037411               13  \n",
+       "29        0.046832               42  \n",
+       "30        0.048430               29  \n",
+       "31        0.048430               29  \n",
+       "32        0.048430               29  \n",
+       "33        0.048777               11  \n",
+       "34        0.048430               29  \n",
+       "35        0.037411               17  \n",
+       "36        0.037411               17  \n",
+       "37        0.037411               17  \n",
+       "38        0.037411               17  \n",
+       "39        0.036842               35  \n",
+       "40        0.036380                3  \n",
+       "41        0.036842               35  \n",
+       "42        0.036842               35  \n",
+       "43        0.048787               44  \n",
+       "44        0.048787               44  \n",
+       "45        0.048787               44  \n",
+       "46        0.046832               42  \n",
+       "47        0.034594               44  \n",
+       "48        0.034594               44  \n",
+       "49        0.034594               44  "
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Obtain results from grid search\n",
+    "accuracy_grid = pd.DataFrame(wine_tune_grid.cv_results_)\n",
+    "accuracy_grid"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "847fd317",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Create the plot\n",
+    "plt.figure(figsize=(10, 6))\n",
+    "\n",
+    "# Plot mean test scores with error bars\n",
+    "plt.plot(accuracy_grid['param_n_neighbors'], accuracy_grid['mean_test_score'], '-o', color='blue')\n",
+    "\n",
+    "# Add labels and legend\n",
+    "plt.xlabel('Number of Neighbors')\n",
+    "plt.ylabel('Accuracy estimate')\n",
+    "plt.title('K-Nearest Neighbors Performance')\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "17201f44",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'n_neighbors': 7}"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Number of neighbors with the highest accuracy programmatically\n",
+    "wine_tune_grid.best_params_"
    ]
   },
   {
@@ -305,12 +3032,1696 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 18,
    "id": "ffefa9f2",
    "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<style>#sk-container-id-2 {\n",
+       "  /* Definition of color scheme common for light and dark mode */\n",
+       "  --sklearn-color-text: #000;\n",
+       "  --sklearn-color-text-muted: #666;\n",
+       "  --sklearn-color-line: gray;\n",
+       "  /* Definition of color scheme for unfitted estimators */\n",
+       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
+       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
+       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
+       "  --sklearn-color-unfitted-level-3: chocolate;\n",
+       "  /* Definition of color scheme for fitted estimators */\n",
+       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
+       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
+       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
+       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
+       "\n",
+       "  /* Specific color for light theme */\n",
+       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
+       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+       "  --sklearn-color-icon: #696969;\n",
+       "\n",
+       "  @media (prefers-color-scheme: dark) {\n",
+       "    /* Redefinition of color scheme for dark theme */\n",
+       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
+       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+       "    --sklearn-color-icon: #878787;\n",
+       "  }\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 pre {\n",
+       "  padding: 0;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 input.sk-hidden--visually {\n",
+       "  border: 0;\n",
+       "  clip: rect(1px 1px 1px 1px);\n",
+       "  clip: rect(1px, 1px, 1px, 1px);\n",
+       "  height: 1px;\n",
+       "  margin: -1px;\n",
+       "  overflow: hidden;\n",
+       "  padding: 0;\n",
+       "  position: absolute;\n",
+       "  width: 1px;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-dashed-wrapped {\n",
+       "  border: 1px dashed var(--sklearn-color-line);\n",
+       "  margin: 0 0.4em 0.5em 0.4em;\n",
+       "  box-sizing: border-box;\n",
+       "  padding-bottom: 0.4em;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-container {\n",
+       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+       "     so we also need the `!important` here to be able to override the\n",
+       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+       "  display: inline-block !important;\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-text-repr-fallback {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-parallel-item,\n",
+       "div.sk-serial,\n",
+       "div.sk-item {\n",
+       "  /* draw centered vertical line to link estimators */\n",
+       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+       "  background-size: 2px 100%;\n",
+       "  background-repeat: no-repeat;\n",
+       "  background-position: center center;\n",
+       "}\n",
+       "\n",
+       "/* Parallel-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-2 div.sk-parallel-item::after {\n",
+       "  content: \"\";\n",
+       "  width: 100%;\n",
+       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+       "  flex-grow: 1;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-parallel {\n",
+       "  display: flex;\n",
+       "  align-items: stretch;\n",
+       "  justify-content: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-parallel-item {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-parallel-item:first-child::after {\n",
+       "  align-self: flex-end;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-parallel-item:last-child::after {\n",
+       "  align-self: flex-start;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-parallel-item:only-child::after {\n",
+       "  width: 0;\n",
+       "}\n",
+       "\n",
+       "/* Serial-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-2 div.sk-serial {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "  align-items: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  padding-right: 1em;\n",
+       "  padding-left: 1em;\n",
+       "}\n",
+       "\n",
+       "\n",
+       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+       "clickable and can be expanded/collapsed.\n",
+       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
+       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+       "*/\n",
+       "\n",
+       "/* Pipeline and ColumnTransformer style (default) */\n",
+       "\n",
+       "#sk-container-id-2 div.sk-toggleable {\n",
+       "  /* Default theme specific background. It is overwritten whether we have a\n",
+       "  specific estimator or a Pipeline/ColumnTransformer */\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable label */\n",
+       "#sk-container-id-2 label.sk-toggleable__label {\n",
+       "  cursor: pointer;\n",
+       "  display: flex;\n",
+       "  width: 100%;\n",
+       "  margin-bottom: 0;\n",
+       "  padding: 0.5em;\n",
+       "  box-sizing: border-box;\n",
+       "  text-align: center;\n",
+       "  align-items: start;\n",
+       "  justify-content: space-between;\n",
+       "  gap: 0.5em;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 label.sk-toggleable__label .caption {\n",
+       "  font-size: 0.6rem;\n",
+       "  font-weight: lighter;\n",
+       "  color: var(--sklearn-color-text-muted);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 label.sk-toggleable__label-arrow:before {\n",
+       "  /* Arrow on the left of the label */\n",
+       "  content: \"▸\";\n",
+       "  float: left;\n",
+       "  margin-right: 0.25em;\n",
+       "  color: var(--sklearn-color-icon);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable content - dropdown */\n",
+       "\n",
+       "#sk-container-id-2 div.sk-toggleable__content {\n",
+       "  display: none;\n",
+       "  text-align: left;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-toggleable__content.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-toggleable__content pre {\n",
+       "  margin: 0.2em;\n",
+       "  border-radius: 0.25em;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-toggleable__content.fitted pre {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+       "  /* Expand drop-down */\n",
+       "  display: block;\n",
+       "  width: 100%;\n",
+       "  overflow: visible;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+       "  content: \"▾\";\n",
+       "}\n",
+       "\n",
+       "/* Pipeline/ColumnTransformer-specific style */\n",
+       "\n",
+       "#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific style */\n",
+       "\n",
+       "/* Colorize estimator box */\n",
+       "#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-label label.sk-toggleable__label,\n",
+       "#sk-container-id-2 div.sk-label label {\n",
+       "  /* The background is the default theme color */\n",
+       "  color: var(--sklearn-color-text-on-default-background);\n",
+       "}\n",
+       "\n",
+       "/* On hover, darken the color of the background */\n",
+       "#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Label box, darken color on hover, fitted */\n",
+       "#sk-container-id-2 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator label */\n",
+       "\n",
+       "#sk-container-id-2 div.sk-label label {\n",
+       "  font-family: monospace;\n",
+       "  font-weight: bold;\n",
+       "  display: inline-block;\n",
+       "  line-height: 1.2em;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-label-container {\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific */\n",
+       "#sk-container-id-2 div.sk-estimator {\n",
+       "  font-family: monospace;\n",
+       "  border: 1px dotted var(--sklearn-color-border-box);\n",
+       "  border-radius: 0.25em;\n",
+       "  box-sizing: border-box;\n",
+       "  margin-bottom: 0.5em;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-estimator.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "/* on hover */\n",
+       "#sk-container-id-2 div.sk-estimator:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-estimator.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
+       "\n",
+       "/* Common style for \"i\" and \"?\" */\n",
+       "\n",
+       ".sk-estimator-doc-link,\n",
+       "a:link.sk-estimator-doc-link,\n",
+       "a:visited.sk-estimator-doc-link {\n",
+       "  float: right;\n",
+       "  font-size: smaller;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  border-radius: 1em;\n",
+       "  height: 1em;\n",
+       "  width: 1em;\n",
+       "  text-decoration: none !important;\n",
+       "  margin-left: 0.5em;\n",
+       "  text-align: center;\n",
+       "  /* unfitted */\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted,\n",
+       "a:link.sk-estimator-doc-link.fitted,\n",
+       "a:visited.sk-estimator-doc-link.fitted {\n",
+       "  /* fitted */\n",
+       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-1);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "/* Span, style for the box shown on hovering the info icon */\n",
+       ".sk-estimator-doc-link span {\n",
+       "  display: none;\n",
+       "  z-index: 9999;\n",
+       "  position: relative;\n",
+       "  font-weight: normal;\n",
+       "  right: .2ex;\n",
+       "  padding: .5ex;\n",
+       "  margin: .5ex;\n",
+       "  width: min-content;\n",
+       "  min-width: 20ex;\n",
+       "  max-width: 50ex;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  box-shadow: 2pt 2pt 4pt #999;\n",
+       "  /* unfitted */\n",
+       "  background: var(--sklearn-color-unfitted-level-0);\n",
+       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted span {\n",
+       "  /* fitted */\n",
+       "  background: var(--sklearn-color-fitted-level-0);\n",
+       "  border: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link:hover span {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
+       "\n",
+       "#sk-container-id-2 a.estimator_doc_link {\n",
+       "  float: right;\n",
+       "  font-size: 1rem;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  border-radius: 1rem;\n",
+       "  height: 1rem;\n",
+       "  width: 1rem;\n",
+       "  text-decoration: none;\n",
+       "  /* unfitted */\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 a.estimator_doc_link.fitted {\n",
+       "  /* fitted */\n",
+       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-1);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "#sk-container-id-2 a.estimator_doc_link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 a.estimator_doc_link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".estimator-table summary {\n",
+       "    padding: .5rem;\n",
+       "    font-family: monospace;\n",
+       "    cursor: pointer;\n",
+       "}\n",
+       "\n",
+       ".estimator-table details[open] {\n",
+       "    padding-left: 0.1rem;\n",
+       "    padding-right: 0.1rem;\n",
+       "    padding-bottom: 0.3rem;\n",
+       "}\n",
+       "\n",
+       ".estimator-table .parameters-table {\n",
+       "    margin-left: auto !important;\n",
+       "    margin-right: auto !important;\n",
+       "}\n",
+       "\n",
+       ".estimator-table .parameters-table tr:nth-child(odd) {\n",
+       "    background-color: #fff;\n",
+       "}\n",
+       "\n",
+       ".estimator-table .parameters-table tr:nth-child(even) {\n",
+       "    background-color: #f6f6f6;\n",
+       "}\n",
+       "\n",
+       ".estimator-table .parameters-table tr:hover {\n",
+       "    background-color: #e0e0e0;\n",
+       "}\n",
+       "\n",
+       ".estimator-table table td {\n",
+       "    border: 1px solid rgba(106, 105, 104, 0.232);\n",
+       "}\n",
+       "\n",
+       ".user-set td {\n",
+       "    color:rgb(255, 94, 0);\n",
+       "    text-align: left;\n",
+       "}\n",
+       "\n",
+       ".user-set td.value pre {\n",
+       "    color:rgb(255, 94, 0) !important;\n",
+       "    background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".default td {\n",
+       "    color: black;\n",
+       "    text-align: left;\n",
+       "}\n",
+       "\n",
+       ".user-set td i,\n",
+       ".default td i {\n",
+       "    color: black;\n",
+       "}\n",
+       "\n",
+       ".copy-paste-icon {\n",
+       "    background-image: url(data:image/svg+xml;base64,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);\n",
+       "    background-repeat: no-repeat;\n",
+       "    background-size: 14px 14px;\n",
+       "    background-position: 0;\n",
+       "    display: inline-block;\n",
+       "    width: 14px;\n",
+       "    height: 14px;\n",
+       "    cursor: pointer;\n",
+       "}\n",
+       "</style><body><div id=\"sk-container-id-2\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>KNeighborsClassifier(n_neighbors=7)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-4\" type=\"checkbox\" checked><label for=\"sk-estimator-id-4\" class=\"sk-toggleable__label  sk-toggleable__label-arrow\"><div><div>KNeighborsClassifier</div></div><div><a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.7/modules/generated/sklearn.neighbors.KNeighborsClassifier.html\">?<span>Documentation for KNeighborsClassifier</span></a><span class=\"sk-estimator-doc-link \">i<span>Not fitted</span></span></div></label><div class=\"sk-toggleable__content \" data-param-prefix=\"\">\n",
+       "        <div class=\"estimator-table\">\n",
+       "            <details>\n",
+       "                <summary>Parameters</summary>\n",
+       "                <table class=\"parameters-table\">\n",
+       "                  <tbody>\n",
+       "                    \n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('n_neighbors',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">n_neighbors&nbsp;</td>\n",
+       "            <td class=\"value\">7</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('weights',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">weights&nbsp;</td>\n",
+       "            <td class=\"value\">&#x27;uniform&#x27;</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('algorithm',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">algorithm&nbsp;</td>\n",
+       "            <td class=\"value\">&#x27;auto&#x27;</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('leaf_size',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">leaf_size&nbsp;</td>\n",
+       "            <td class=\"value\">30</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('p',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">p&nbsp;</td>\n",
+       "            <td class=\"value\">2</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('metric',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">metric&nbsp;</td>\n",
+       "            <td class=\"value\">&#x27;minkowski&#x27;</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('metric_params',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">metric_params&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('n_jobs',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">n_jobs&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "                  </tbody>\n",
+       "                </table>\n",
+       "            </details>\n",
+       "        </div>\n",
+       "    </div></div></div></div></div><script>function copyToClipboard(text, element) {\n",
+       "    // Get the parameter prefix from the closest toggleable content\n",
+       "    const toggleableContent = element.closest('.sk-toggleable__content');\n",
+       "    const paramPrefix = toggleableContent ? toggleableContent.dataset.paramPrefix : '';\n",
+       "    const fullParamName = paramPrefix ? `${paramPrefix}${text}` : text;\n",
+       "\n",
+       "    const originalStyle = element.style;\n",
+       "    const computedStyle = window.getComputedStyle(element);\n",
+       "    const originalWidth = computedStyle.width;\n",
+       "    const originalHTML = element.innerHTML.replace('Copied!', '');\n",
+       "\n",
+       "    navigator.clipboard.writeText(fullParamName)\n",
+       "        .then(() => {\n",
+       "            element.style.width = originalWidth;\n",
+       "            element.style.color = 'green';\n",
+       "            element.innerHTML = \"Copied!\";\n",
+       "\n",
+       "            setTimeout(() => {\n",
+       "                element.innerHTML = originalHTML;\n",
+       "                element.style = originalStyle;\n",
+       "            }, 2000);\n",
+       "        })\n",
+       "        .catch(err => {\n",
+       "            console.error('Failed to copy:', err);\n",
+       "            element.style.color = 'red';\n",
+       "            element.innerHTML = \"Failed!\";\n",
+       "            setTimeout(() => {\n",
+       "                element.innerHTML = originalHTML;\n",
+       "                element.style = originalStyle;\n",
+       "            }, 2000);\n",
+       "        });\n",
+       "    return false;\n",
+       "}\n",
+       "\n",
+       "document.querySelectorAll('.fa-regular.fa-copy').forEach(function(element) {\n",
+       "    const toggleableContent = element.closest('.sk-toggleable__content');\n",
+       "    const paramPrefix = toggleableContent ? toggleableContent.dataset.paramPrefix : '';\n",
+       "    const paramName = element.parentElement.nextElementSibling.textContent.trim();\n",
+       "    const fullParamName = paramPrefix ? `${paramPrefix}${paramName}` : paramName;\n",
+       "\n",
+       "    element.setAttribute('title', fullParamName);\n",
+       "});\n",
+       "</script></body>"
+      ],
+      "text/plain": [
+       "KNeighborsClassifier(n_neighbors=7)"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Initialize the KNN classifier using K=7\n",
+    "knn = KNeighborsClassifier(n_neighbors=7)\n",
+    "knn"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "09d4f70c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<style>#sk-container-id-3 {\n",
+       "  /* Definition of color scheme common for light and dark mode */\n",
+       "  --sklearn-color-text: #000;\n",
+       "  --sklearn-color-text-muted: #666;\n",
+       "  --sklearn-color-line: gray;\n",
+       "  /* Definition of color scheme for unfitted estimators */\n",
+       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
+       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
+       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
+       "  --sklearn-color-unfitted-level-3: chocolate;\n",
+       "  /* Definition of color scheme for fitted estimators */\n",
+       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
+       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
+       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
+       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
+       "\n",
+       "  /* Specific color for light theme */\n",
+       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
+       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+       "  --sklearn-color-icon: #696969;\n",
+       "\n",
+       "  @media (prefers-color-scheme: dark) {\n",
+       "    /* Redefinition of color scheme for dark theme */\n",
+       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
+       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+       "    --sklearn-color-icon: #878787;\n",
+       "  }\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 pre {\n",
+       "  padding: 0;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 input.sk-hidden--visually {\n",
+       "  border: 0;\n",
+       "  clip: rect(1px 1px 1px 1px);\n",
+       "  clip: rect(1px, 1px, 1px, 1px);\n",
+       "  height: 1px;\n",
+       "  margin: -1px;\n",
+       "  overflow: hidden;\n",
+       "  padding: 0;\n",
+       "  position: absolute;\n",
+       "  width: 1px;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-dashed-wrapped {\n",
+       "  border: 1px dashed var(--sklearn-color-line);\n",
+       "  margin: 0 0.4em 0.5em 0.4em;\n",
+       "  box-sizing: border-box;\n",
+       "  padding-bottom: 0.4em;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-container {\n",
+       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+       "     so we also need the `!important` here to be able to override the\n",
+       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+       "  display: inline-block !important;\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-text-repr-fallback {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-parallel-item,\n",
+       "div.sk-serial,\n",
+       "div.sk-item {\n",
+       "  /* draw centered vertical line to link estimators */\n",
+       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+       "  background-size: 2px 100%;\n",
+       "  background-repeat: no-repeat;\n",
+       "  background-position: center center;\n",
+       "}\n",
+       "\n",
+       "/* Parallel-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-3 div.sk-parallel-item::after {\n",
+       "  content: \"\";\n",
+       "  width: 100%;\n",
+       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+       "  flex-grow: 1;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-parallel {\n",
+       "  display: flex;\n",
+       "  align-items: stretch;\n",
+       "  justify-content: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-parallel-item {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-parallel-item:first-child::after {\n",
+       "  align-self: flex-end;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-parallel-item:last-child::after {\n",
+       "  align-self: flex-start;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-parallel-item:only-child::after {\n",
+       "  width: 0;\n",
+       "}\n",
+       "\n",
+       "/* Serial-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-3 div.sk-serial {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "  align-items: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  padding-right: 1em;\n",
+       "  padding-left: 1em;\n",
+       "}\n",
+       "\n",
+       "\n",
+       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+       "clickable and can be expanded/collapsed.\n",
+       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
+       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+       "*/\n",
+       "\n",
+       "/* Pipeline and ColumnTransformer style (default) */\n",
+       "\n",
+       "#sk-container-id-3 div.sk-toggleable {\n",
+       "  /* Default theme specific background. It is overwritten whether we have a\n",
+       "  specific estimator or a Pipeline/ColumnTransformer */\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable label */\n",
+       "#sk-container-id-3 label.sk-toggleable__label {\n",
+       "  cursor: pointer;\n",
+       "  display: flex;\n",
+       "  width: 100%;\n",
+       "  margin-bottom: 0;\n",
+       "  padding: 0.5em;\n",
+       "  box-sizing: border-box;\n",
+       "  text-align: center;\n",
+       "  align-items: start;\n",
+       "  justify-content: space-between;\n",
+       "  gap: 0.5em;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 label.sk-toggleable__label .caption {\n",
+       "  font-size: 0.6rem;\n",
+       "  font-weight: lighter;\n",
+       "  color: var(--sklearn-color-text-muted);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 label.sk-toggleable__label-arrow:before {\n",
+       "  /* Arrow on the left of the label */\n",
+       "  content: \"▸\";\n",
+       "  float: left;\n",
+       "  margin-right: 0.25em;\n",
+       "  color: var(--sklearn-color-icon);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 label.sk-toggleable__label-arrow:hover:before {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable content - dropdown */\n",
+       "\n",
+       "#sk-container-id-3 div.sk-toggleable__content {\n",
+       "  display: none;\n",
+       "  text-align: left;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-toggleable__content.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-toggleable__content pre {\n",
+       "  margin: 0.2em;\n",
+       "  border-radius: 0.25em;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-toggleable__content.fitted pre {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+       "  /* Expand drop-down */\n",
+       "  display: block;\n",
+       "  width: 100%;\n",
+       "  overflow: visible;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+       "  content: \"▾\";\n",
+       "}\n",
+       "\n",
+       "/* Pipeline/ColumnTransformer-specific style */\n",
+       "\n",
+       "#sk-container-id-3 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific style */\n",
+       "\n",
+       "/* Colorize estimator box */\n",
+       "#sk-container-id-3 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-label label.sk-toggleable__label,\n",
+       "#sk-container-id-3 div.sk-label label {\n",
+       "  /* The background is the default theme color */\n",
+       "  color: var(--sklearn-color-text-on-default-background);\n",
+       "}\n",
+       "\n",
+       "/* On hover, darken the color of the background */\n",
+       "#sk-container-id-3 div.sk-label:hover label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Label box, darken color on hover, fitted */\n",
+       "#sk-container-id-3 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator label */\n",
+       "\n",
+       "#sk-container-id-3 div.sk-label label {\n",
+       "  font-family: monospace;\n",
+       "  font-weight: bold;\n",
+       "  display: inline-block;\n",
+       "  line-height: 1.2em;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-label-container {\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific */\n",
+       "#sk-container-id-3 div.sk-estimator {\n",
+       "  font-family: monospace;\n",
+       "  border: 1px dotted var(--sklearn-color-border-box);\n",
+       "  border-radius: 0.25em;\n",
+       "  box-sizing: border-box;\n",
+       "  margin-bottom: 0.5em;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-estimator.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "/* on hover */\n",
+       "#sk-container-id-3 div.sk-estimator:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-estimator.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
+       "\n",
+       "/* Common style for \"i\" and \"?\" */\n",
+       "\n",
+       ".sk-estimator-doc-link,\n",
+       "a:link.sk-estimator-doc-link,\n",
+       "a:visited.sk-estimator-doc-link {\n",
+       "  float: right;\n",
+       "  font-size: smaller;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  border-radius: 1em;\n",
+       "  height: 1em;\n",
+       "  width: 1em;\n",
+       "  text-decoration: none !important;\n",
+       "  margin-left: 0.5em;\n",
+       "  text-align: center;\n",
+       "  /* unfitted */\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted,\n",
+       "a:link.sk-estimator-doc-link.fitted,\n",
+       "a:visited.sk-estimator-doc-link.fitted {\n",
+       "  /* fitted */\n",
+       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-1);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "/* Span, style for the box shown on hovering the info icon */\n",
+       ".sk-estimator-doc-link span {\n",
+       "  display: none;\n",
+       "  z-index: 9999;\n",
+       "  position: relative;\n",
+       "  font-weight: normal;\n",
+       "  right: .2ex;\n",
+       "  padding: .5ex;\n",
+       "  margin: .5ex;\n",
+       "  width: min-content;\n",
+       "  min-width: 20ex;\n",
+       "  max-width: 50ex;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  box-shadow: 2pt 2pt 4pt #999;\n",
+       "  /* unfitted */\n",
+       "  background: var(--sklearn-color-unfitted-level-0);\n",
+       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted span {\n",
+       "  /* fitted */\n",
+       "  background: var(--sklearn-color-fitted-level-0);\n",
+       "  border: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link:hover span {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
+       "\n",
+       "#sk-container-id-3 a.estimator_doc_link {\n",
+       "  float: right;\n",
+       "  font-size: 1rem;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  border-radius: 1rem;\n",
+       "  height: 1rem;\n",
+       "  width: 1rem;\n",
+       "  text-decoration: none;\n",
+       "  /* unfitted */\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 a.estimator_doc_link.fitted {\n",
+       "  /* fitted */\n",
+       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-1);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "#sk-container-id-3 a.estimator_doc_link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 a.estimator_doc_link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".estimator-table summary {\n",
+       "    padding: .5rem;\n",
+       "    font-family: monospace;\n",
+       "    cursor: pointer;\n",
+       "}\n",
+       "\n",
+       ".estimator-table details[open] {\n",
+       "    padding-left: 0.1rem;\n",
+       "    padding-right: 0.1rem;\n",
+       "    padding-bottom: 0.3rem;\n",
+       "}\n",
+       "\n",
+       ".estimator-table .parameters-table {\n",
+       "    margin-left: auto !important;\n",
+       "    margin-right: auto !important;\n",
+       "}\n",
+       "\n",
+       ".estimator-table .parameters-table tr:nth-child(odd) {\n",
+       "    background-color: #fff;\n",
+       "}\n",
+       "\n",
+       ".estimator-table .parameters-table tr:nth-child(even) {\n",
+       "    background-color: #f6f6f6;\n",
+       "}\n",
+       "\n",
+       ".estimator-table .parameters-table tr:hover {\n",
+       "    background-color: #e0e0e0;\n",
+       "}\n",
+       "\n",
+       ".estimator-table table td {\n",
+       "    border: 1px solid rgba(106, 105, 104, 0.232);\n",
+       "}\n",
+       "\n",
+       ".user-set td {\n",
+       "    color:rgb(255, 94, 0);\n",
+       "    text-align: left;\n",
+       "}\n",
+       "\n",
+       ".user-set td.value pre {\n",
+       "    color:rgb(255, 94, 0) !important;\n",
+       "    background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".default td {\n",
+       "    color: black;\n",
+       "    text-align: left;\n",
+       "}\n",
+       "\n",
+       ".user-set td i,\n",
+       ".default td i {\n",
+       "    color: black;\n",
+       "}\n",
+       "\n",
+       ".copy-paste-icon {\n",
+       "    background-image: url(data:image/svg+xml;base64,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);\n",
+       "    background-repeat: no-repeat;\n",
+       "    background-size: 14px 14px;\n",
+       "    background-position: 0;\n",
+       "    display: inline-block;\n",
+       "    width: 14px;\n",
+       "    height: 14px;\n",
+       "    cursor: pointer;\n",
+       "}\n",
+       "</style><body><div id=\"sk-container-id-3\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>KNeighborsClassifier(n_neighbors=7)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-5\" type=\"checkbox\" checked><label for=\"sk-estimator-id-5\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow\"><div><div>KNeighborsClassifier</div></div><div><a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.7/modules/generated/sklearn.neighbors.KNeighborsClassifier.html\">?<span>Documentation for KNeighborsClassifier</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></div></label><div class=\"sk-toggleable__content fitted\" data-param-prefix=\"\">\n",
+       "        <div class=\"estimator-table\">\n",
+       "            <details>\n",
+       "                <summary>Parameters</summary>\n",
+       "                <table class=\"parameters-table\">\n",
+       "                  <tbody>\n",
+       "                    \n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('n_neighbors',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">n_neighbors&nbsp;</td>\n",
+       "            <td class=\"value\">7</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('weights',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">weights&nbsp;</td>\n",
+       "            <td class=\"value\">&#x27;uniform&#x27;</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('algorithm',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">algorithm&nbsp;</td>\n",
+       "            <td class=\"value\">&#x27;auto&#x27;</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('leaf_size',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">leaf_size&nbsp;</td>\n",
+       "            <td class=\"value\">30</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('p',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">p&nbsp;</td>\n",
+       "            <td class=\"value\">2</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('metric',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">metric&nbsp;</td>\n",
+       "            <td class=\"value\">&#x27;minkowski&#x27;</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('metric_params',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">metric_params&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('n_jobs',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">n_jobs&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "                  </tbody>\n",
+       "                </table>\n",
+       "            </details>\n",
+       "        </div>\n",
+       "    </div></div></div></div></div><script>function copyToClipboard(text, element) {\n",
+       "    // Get the parameter prefix from the closest toggleable content\n",
+       "    const toggleableContent = element.closest('.sk-toggleable__content');\n",
+       "    const paramPrefix = toggleableContent ? toggleableContent.dataset.paramPrefix : '';\n",
+       "    const fullParamName = paramPrefix ? `${paramPrefix}${text}` : text;\n",
+       "\n",
+       "    const originalStyle = element.style;\n",
+       "    const computedStyle = window.getComputedStyle(element);\n",
+       "    const originalWidth = computedStyle.width;\n",
+       "    const originalHTML = element.innerHTML.replace('Copied!', '');\n",
+       "\n",
+       "    navigator.clipboard.writeText(fullParamName)\n",
+       "        .then(() => {\n",
+       "            element.style.width = originalWidth;\n",
+       "            element.style.color = 'green';\n",
+       "            element.innerHTML = \"Copied!\";\n",
+       "\n",
+       "            setTimeout(() => {\n",
+       "                element.innerHTML = originalHTML;\n",
+       "                element.style = originalStyle;\n",
+       "            }, 2000);\n",
+       "        })\n",
+       "        .catch(err => {\n",
+       "            console.error('Failed to copy:', err);\n",
+       "            element.style.color = 'red';\n",
+       "            element.innerHTML = \"Failed!\";\n",
+       "            setTimeout(() => {\n",
+       "                element.innerHTML = originalHTML;\n",
+       "                element.style = originalStyle;\n",
+       "            }, 2000);\n",
+       "        });\n",
+       "    return false;\n",
+       "}\n",
+       "\n",
+       "document.querySelectorAll('.fa-regular.fa-copy').forEach(function(element) {\n",
+       "    const toggleableContent = element.closest('.sk-toggleable__content');\n",
+       "    const paramPrefix = toggleableContent ? toggleableContent.dataset.paramPrefix : '';\n",
+       "    const paramName = element.parentElement.nextElementSibling.textContent.trim();\n",
+       "    const fullParamName = paramPrefix ? `${paramPrefix}${paramName}` : paramName;\n",
+       "\n",
+       "    element.setAttribute('title', fullParamName);\n",
+       "});\n",
+       "</script></body>"
+      ],
+      "text/plain": [
+       "KNeighborsClassifier(n_neighbors=7)"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Fit the model on the wine training data using the define values of the X and y training data\n",
+    "knn.fit(X=X_train, y=y_train)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "8026d4ad",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>alcohol</th>\n",
+       "      <th>malic_acid</th>\n",
+       "      <th>ash</th>\n",
+       "      <th>alcalinity_of_ash</th>\n",
+       "      <th>magnesium</th>\n",
+       "      <th>total_phenols</th>\n",
+       "      <th>flavanoids</th>\n",
+       "      <th>nonflavanoid_phenols</th>\n",
+       "      <th>proanthocyanins</th>\n",
+       "      <th>color_intensity</th>\n",
+       "      <th>hue</th>\n",
+       "      <th>od280/od315_of_diluted_wines</th>\n",
+       "      <th>proline</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>78</th>\n",
+       "      <td>-0.828391</td>\n",
+       "      <td>-1.208567</td>\n",
+       "      <td>-1.522511</td>\n",
+       "      <td>-1.409821</td>\n",
+       "      <td>2.545825</td>\n",
+       "      <td>-0.633101</td>\n",
+       "      <td>-0.179981</td>\n",
+       "      <td>-0.095517</td>\n",
+       "      <td>2.048364</td>\n",
+       "      <td>-0.717240</td>\n",
+       "      <td>0.449924</td>\n",
+       "      <td>-0.426113</td>\n",
+       "      <td>0.009893</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1.518613</td>\n",
+       "      <td>-0.562250</td>\n",
+       "      <td>0.232053</td>\n",
+       "      <td>-1.169593</td>\n",
+       "      <td>1.913905</td>\n",
+       "      <td>0.808997</td>\n",
+       "      <td>1.034819</td>\n",
+       "      <td>-0.659563</td>\n",
+       "      <td>1.224884</td>\n",
+       "      <td>0.251717</td>\n",
+       "      <td>0.362177</td>\n",
+       "      <td>1.847920</td>\n",
+       "      <td>1.013009</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>0.777454</td>\n",
+       "      <td>-0.472483</td>\n",
+       "      <td>1.218995</td>\n",
+       "      <td>-0.689137</td>\n",
+       "      <td>0.860705</td>\n",
+       "      <td>0.889114</td>\n",
+       "      <td>0.884224</td>\n",
+       "      <td>-0.498407</td>\n",
+       "      <td>-0.229346</td>\n",
+       "      <td>0.969783</td>\n",
+       "      <td>1.415139</td>\n",
+       "      <td>0.378979</td>\n",
+       "      <td>1.793210</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>2.160950</td>\n",
+       "      <td>-0.544297</td>\n",
+       "      <td>0.085839</td>\n",
+       "      <td>-2.430790</td>\n",
+       "      <td>-0.613775</td>\n",
+       "      <td>1.289697</td>\n",
+       "      <td>1.667318</td>\n",
+       "      <td>0.549108</td>\n",
+       "      <td>2.135968</td>\n",
+       "      <td>0.147900</td>\n",
+       "      <td>1.283518</td>\n",
+       "      <td>0.167113</td>\n",
+       "      <td>1.283691</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>1.703902</td>\n",
+       "      <td>-0.418624</td>\n",
+       "      <td>0.049285</td>\n",
+       "      <td>-2.250619</td>\n",
+       "      <td>0.158572</td>\n",
+       "      <td>1.610163</td>\n",
+       "      <td>1.617120</td>\n",
+       "      <td>-0.578985</td>\n",
+       "      <td>2.398780</td>\n",
+       "      <td>1.056297</td>\n",
+       "      <td>1.064151</td>\n",
+       "      <td>0.548472</td>\n",
+       "      <td>2.547935</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>112</th>\n",
+       "      <td>-1.532492</td>\n",
+       "      <td>0.308483</td>\n",
+       "      <td>2.023170</td>\n",
+       "      <td>0.151661</td>\n",
+       "      <td>0.228785</td>\n",
+       "      <td>-0.873451</td>\n",
+       "      <td>0.000733</td>\n",
+       "      <td>1.918935</td>\n",
+       "      <td>-0.947700</td>\n",
+       "      <td>-0.544212</td>\n",
+       "      <td>1.195772</td>\n",
+       "      <td>-0.157749</td>\n",
+       "      <td>-0.445489</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>101</th>\n",
+       "      <td>-0.494869</td>\n",
+       "      <td>-0.894385</td>\n",
+       "      <td>-1.705278</td>\n",
+       "      <td>-0.298767</td>\n",
+       "      <td>-0.824415</td>\n",
+       "      <td>-1.354150</td>\n",
+       "      <td>-0.671924</td>\n",
+       "      <td>-0.578985</td>\n",
+       "      <td>-0.422075</td>\n",
+       "      <td>-1.128181</td>\n",
+       "      <td>0.362177</td>\n",
+       "      <td>0.223610</td>\n",
+       "      <td>-0.588791</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>0.925685</td>\n",
+       "      <td>-0.544297</td>\n",
+       "      <td>0.158946</td>\n",
+       "      <td>-1.049479</td>\n",
+       "      <td>-0.754202</td>\n",
+       "      <td>0.488531</td>\n",
+       "      <td>0.733629</td>\n",
+       "      <td>-0.578985</td>\n",
+       "      <td>0.383884</td>\n",
+       "      <td>0.234414</td>\n",
+       "      <td>0.844785</td>\n",
+       "      <td>0.407228</td>\n",
+       "      <td>1.825055</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>61</th>\n",
+       "      <td>-0.445459</td>\n",
+       "      <td>-0.876432</td>\n",
+       "      <td>-1.266637</td>\n",
+       "      <td>-0.809251</td>\n",
+       "      <td>0.018145</td>\n",
+       "      <td>-0.440821</td>\n",
+       "      <td>-0.621726</td>\n",
+       "      <td>1.354888</td>\n",
+       "      <td>-1.701097</td>\n",
+       "      <td>0.299300</td>\n",
+       "      <td>0.098937</td>\n",
+       "      <td>-1.443072</td>\n",
+       "      <td>-0.945455</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>66</th>\n",
+       "      <td>0.135116</td>\n",
+       "      <td>-1.190614</td>\n",
+       "      <td>-2.436346</td>\n",
+       "      <td>-1.349764</td>\n",
+       "      <td>-1.526548</td>\n",
+       "      <td>1.097417</td>\n",
+       "      <td>1.155295</td>\n",
+       "      <td>-0.820719</td>\n",
+       "      <td>1.207363</td>\n",
+       "      <td>0.104643</td>\n",
+       "      <td>0.713164</td>\n",
+       "      <td>0.802712</td>\n",
+       "      <td>-0.779861</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>133 rows × 13 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      alcohol  malic_acid       ash  alcalinity_of_ash  magnesium  \\\n",
+       "78  -0.828391   -1.208567 -1.522511          -1.409821   2.545825   \n",
+       "0    1.518613   -0.562250  0.232053          -1.169593   1.913905   \n",
+       "15   0.777454   -0.472483  1.218995          -0.689137   0.860705   \n",
+       "13   2.160950   -0.544297  0.085839          -2.430790  -0.613775   \n",
+       "14   1.703902   -0.418624  0.049285          -2.250619   0.158572   \n",
+       "..        ...         ...       ...                ...        ...   \n",
+       "112 -1.532492    0.308483  2.023170           0.151661   0.228785   \n",
+       "101 -0.494869   -0.894385 -1.705278          -0.298767  -0.824415   \n",
+       "12   0.925685   -0.544297  0.158946          -1.049479  -0.754202   \n",
+       "61  -0.445459   -0.876432 -1.266637          -0.809251   0.018145   \n",
+       "66   0.135116   -1.190614 -2.436346          -1.349764  -1.526548   \n",
+       "\n",
+       "     total_phenols  flavanoids  nonflavanoid_phenols  proanthocyanins  \\\n",
+       "78       -0.633101   -0.179981             -0.095517         2.048364   \n",
+       "0         0.808997    1.034819             -0.659563         1.224884   \n",
+       "15        0.889114    0.884224             -0.498407        -0.229346   \n",
+       "13        1.289697    1.667318              0.549108         2.135968   \n",
+       "14        1.610163    1.617120             -0.578985         2.398780   \n",
+       "..             ...         ...                   ...              ...   \n",
+       "112      -0.873451    0.000733              1.918935        -0.947700   \n",
+       "101      -1.354150   -0.671924             -0.578985        -0.422075   \n",
+       "12        0.488531    0.733629             -0.578985         0.383884   \n",
+       "61       -0.440821   -0.621726              1.354888        -1.701097   \n",
+       "66        1.097417    1.155295             -0.820719         1.207363   \n",
+       "\n",
+       "     color_intensity       hue  od280/od315_of_diluted_wines   proline  \n",
+       "78         -0.717240  0.449924                     -0.426113  0.009893  \n",
+       "0           0.251717  0.362177                      1.847920  1.013009  \n",
+       "15          0.969783  1.415139                      0.378979  1.793210  \n",
+       "13          0.147900  1.283518                      0.167113  1.283691  \n",
+       "14          1.056297  1.064151                      0.548472  2.547935  \n",
+       "..               ...       ...                           ...       ...  \n",
+       "112        -0.544212  1.195772                     -0.157749 -0.445489  \n",
+       "101        -1.128181  0.362177                      0.223610 -0.588791  \n",
+       "12          0.234414  0.844785                      0.407228  1.825055  \n",
+       "61          0.299300  0.098937                     -1.443072 -0.945455  \n",
+       "66          0.104643  0.713164                      0.802712 -0.779861  \n",
+       "\n",
+       "[133 rows x 13 columns]"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "X_train\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "038fd73f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "78     1\n",
+       "0      0\n",
+       "15     0\n",
+       "13     0\n",
+       "14     0\n",
+       "      ..\n",
+       "112    1\n",
+       "101    1\n",
+       "12     0\n",
+       "61     1\n",
+       "66     1\n",
+       "Name: class, Length: 133, dtype: int64"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "y_train"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "03f2e003",
+   "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here..."
+    "# Predict class on the test set using a new variable array called y_pred\n",
+    "# Refer to: https://scikit-learn.org/stable/modules/generated/sklearn.metrics.accuracy_score.html \n",
+    "# Note: \"from sklearn.metrics import accuracy_score\" was imported as part of the standard libraries\n",
+    "y_pred = knn.predict(X_test)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "652dc934",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[1 1 2 0 1 0 1 1 0 2 0 0 1 1 1 1 2 0 1 0 1 0 0 2 2 2 2 2 0 2 1 0 0 1 0 1 2\n",
+      " 0 1 0 0 2 0 2 2]\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(y_pred)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "id": "1e168a0c",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "102    1\n",
+      "84     1\n",
+      "96     1\n",
+      "65     1\n",
+      "79     1\n",
+      "17     0\n",
+      "109    1\n",
+      "113    1\n",
+      "28     0\n",
+      "159    2\n",
+      "38     0\n",
+      "34     0\n",
+      "125    1\n",
+      "115    1\n",
+      "71     1\n",
+      "76     1\n",
+      "131    2\n",
+      "33     0\n",
+      "60     1\n",
+      "19     0\n",
+      "114    1\n",
+      "47     0\n",
+      "48     0\n",
+      "158    2\n",
+      "133    2\n",
+      "137    2\n",
+      "154    2\n",
+      "136    2\n",
+      "2      0\n",
+      "168    2\n",
+      "117    1\n",
+      "32     0\n",
+      "22     0\n",
+      "108    1\n",
+      "73     1\n",
+      "77     1\n",
+      "142    2\n",
+      "9      0\n",
+      "85     1\n",
+      "58     0\n",
+      "45     0\n",
+      "175    2\n",
+      "42     0\n",
+      "143    2\n",
+      "177    2\n",
+      "Name: class, dtype: int64\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(y_test)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "dd49c54f",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0.9333333333333333\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Use accuracy_score function to calculate test KNN classifier model accuracy \n",
+    "# Relies on code in step immediately above\n",
+    "accuracy = accuracy_score(y_pred, y_test)\n",
+    "print(accuracy)\n",
+    " "
    ]
   },
   {
@@ -365,7 +4776,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3.10.4",
+   "display_name": "lcr-env",
    "language": "python",
    "name": "python3"
   },
@@ -379,12 +4790,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
-  },
-  "vscode": {
-   "interpreter": {
-    "hash": "497a84dc8fec8cf8d24e7e87b6d954c9a18a327edc66feb9b9ea7e9e72cc5c7e"
-   }
+   "version": "3.11.13"
   }
  },
  "nbformat": 4,