diff --git a/.gitignore b/.gitignore
index 66ce1bd..629c5f8 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1 +1,2 @@
 .ipynb_checkpoints*
+Notebooks/load_data.ipynb
diff --git a/Notebooks/eda_data.ipynb b/Notebooks/eda_data.ipynb
index 5d5ac14..6aaca53 100644
--- a/Notebooks/eda_data.ipynb
+++ b/Notebooks/eda_data.ipynb
@@ -4,54 +4,19 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Analisis Predictivo de la Edad del Cangrejo 🦀 "
+    "# **Analisis Predictivo de la Edad del Cangrejo 🦀**"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "\n",
-    "Para un criador comercial de cangrejos, conocer la edad correcta del cangrejo les ayuda a decidir si cosechar los cangrejos y cuándo. Más allá de cierta edad, hay un crecimiento insignificante en las características físicas del cangrejo y, por lo tanto, es importante cronometrar la cosecha para reducir el costo y aumentar las ganancias.\n",
-    "\n",
-    "## Descripción de los Datos\n",
-    "Estos Datos fueron extraidos de la plataforma kaggle [Dataset](https://www.kaggle.com/code/umutcindiloglu/crab-age-prediction).\n",
-    "\n",
-    "Este conjunto de datos contiene información sobre diferentes características de los cangrejos. Las variables incluidas son:\n",
-    "\n",
-    "Columnas:\n",
-    "\n",
-    "    •  Sex: Género del cangrejo (Macho, Hembra, Indeterminado).\n",
-    "    •  Length: Longitud del cangrejo (en pies; 1 pie = 30.48 cm).\n",
-    "    •  Diameter: Diámetro del cangrejo (en pies; 1 pie = 30.48 cm).\n",
-    "    •  Height: Altura del cangrejo (en pies; 1 pie = 30.48 cm).\n",
-    "    •  Weight: Peso del cangrejo (en onzas; 1 libra = 16 onzas).\n",
-    "    •  Shucked Weight: Peso del cangrejo sin cáscara (en onzas; 1 libra = 16 onzas).\n",
-    "    •  Viscera Weight: Peso de las vísceras del cangrejo (en onzas; 1 libra = 16 onzas).\n",
-    "    •  Shell Weight: Peso de la cáscara del cangrejo (en onzas; 1 libra = 16 onzas).\n",
-    "    •  Age: Edad del cangrejo (en meses).\n",
-    "Objetivos:\n",
-    "    \n",
-    "+ El primer objetivo es identificar cuáles de las variables disponibles (sexo, longitud, diámetro, altura, peso total, peso sin cáscara, peso de las vísceras y peso de la cáscara) tienen una correlación más fuerte con la edad del cangrejo.\n",
-    "\n",
-    "    > Al identificar las variables más influyentes en la determinación de la edad, podemos enfocarnos en medir y registrar estas variables de manera más precisa y eficiente, reduciendo costos operativos.\n",
-    "    \n",
-    "+ El segundo objetivo es desarrollar un modelo de machine learning que permita predecir la edad de un cangrejo en función de sus características físicas.\n",
-    "\n",
-    "    > Un modelo preciso permitirá a los criadores tomar decisiones más informadas sobre cuándo cosechar los cangrejos, maximizando así sus ganancias.\n",
-    "\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Importamos Librerias"
+    "# **Importamos Librerias**"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 1,
    "metadata": {
     "tags": []
    },
@@ -67,146 +32,13 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Carga de datos"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Downloading from https://www.kaggle.com/api/v1/datasets/download/sidhus/crab-age-prediction?dataset_version_number=1...\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "100%|██████████████████████████████████████| 81.2k/81.2k [00:00<00:00, 33.3MB/s]"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Extracting files...\n",
-      "Path to dataset files: /Users/andres/.cache/kagglehub/datasets/sidhus/crab-age-prediction/versions/1\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\n"
-     ]
-    }
-   ],
-   "source": [
-    "import kagglehub\n",
-    "\n",
-    "# Download latest version\n",
-    "path = kagglehub.dataset_download(\"sidhus/crab-age-prediction\")\n",
-    "\n",
-    "print(\"Path to dataset files:\", path)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 12,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\u001b[01;34m/Users/andres/.cache/kagglehub/datasets/sidhus/\u001b[0m\n",
-      "└── \u001b[01;34mcrab-age-prediction\u001b[0m\n",
-      "    ├── \u001b[00m1.complete\u001b[0m\n",
-      "    └── \u001b[01;34mversions\u001b[0m\n",
-      "        └── \u001b[01;34m1\u001b[0m\n",
-      "            └── \u001b[00mCrabAgePrediction.csv\u001b[0m\n",
-      "\n",
-      "4 directories, 2 files\n"
-     ]
-    }
-   ],
-   "source": [
-    "!tree /Users/andres/.cache/kagglehub/datasets/sidhus/"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 15,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "data = pd.read_csv(path+'/CrabAgePrediction.csv')"
+    "# **Carga de Datos**"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "<class 'pandas.core.frame.DataFrame'>\n",
-      "RangeIndex: 3893 entries, 0 to 3892\n",
-      "Data columns (total 9 columns):\n",
-      " #   Column          Non-Null Count  Dtype  \n",
-      "---  ------          --------------  -----  \n",
-      " 0   Sex             3893 non-null   object \n",
-      " 1   Length          3893 non-null   float64\n",
-      " 2   Diameter        3893 non-null   float64\n",
-      " 3   Height          3893 non-null   float64\n",
-      " 4   Weight          3893 non-null   float64\n",
-      " 5   Shucked Weight  3893 non-null   float64\n",
-      " 6   Viscera Weight  3893 non-null   float64\n",
-      " 7   Shell Weight    3893 non-null   float64\n",
-      " 8   Age             3893 non-null   int64  \n",
-      "dtypes: float64(7), int64(1), object(1)\n",
-      "memory usage: 273.9+ KB\n"
-     ]
-    }
-   ],
-   "source": [
-    "data.info()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "> Contamos con `3893` observaciones y `9` variables, la una varible categoríca con la que contamos es el `Sex`"
-   ]
-  },
-  {
-   "cell_type": "markdown",
+   "execution_count": 2,
    "metadata": {},
-   "source": [
-    "## Veamos los datos en la tabla"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 19,
-   "metadata": {
-    "tags": []
-   },
    "outputs": [
     {
      "data": {
@@ -321,12 +153,14 @@
        "4      1.700970    6  "
       ]
      },
-     "execution_count": 19,
+     "execution_count": 2,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
+    "data = pd.read_csv(\"D:/DataSets/CrabAge/data_CrabAge.csv\")\n",
+    "data.drop(columns = \"Unnamed: 0\", inplace = True)\n",
     "data.head()"
    ]
   },
@@ -334,76 +168,82 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Analisis Exploratorio\n",
-    "!que haremos¡"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 20,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0"
-      ]
-     },
-     "execution_count": 20,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "data.duplicated().sum()"
+    "> - Age (Edad): Edad del cangrejo (en meses)\n",
+    "\n",
+    "> - Sex (Sexo): Sexo del cangrejo; Femenino (F), masculino (M) o indeterminado (I).\n",
+    "\n",
+    "> - length (largo): Largo del cangrejo (en pies; 1 pie = 30.48 cm).\n",
+    "\n",
+    "> - Diameter (Diametro): Diametro del cangrejo (en pies; 1 pie = 30.48 cm).\n",
+    "\n",
+    "> - Height (Altura): Altura del cangrejo (en pies; 1 pie = 30.48 cm).\n",
+    "\n",
+    "> - Weight (Peso): Peso del cangrejo (en onzas; 1 libra = 16 onzas).\n",
+    "\n",
+    "> - Shucked Weight (Peso Descascarado): Peso del cangrejo sin cascarón (en onzas; 1 libra = 16 onzas).\n",
+    "\n",
+    "> - Viscera Weight (Peso de las Visceras): Peso de las visceras del cangrejo (en onzas; 1 libra = 16 onzas).\n",
+    "\n",
+    "> - Shell Weight (Peso de la Concha): Peso del cascarón del cangrejo (en onzas; 1 libra = 16 onzas)."
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "No hay valores duplicados"
+    "# **Análisis Exploratorio**\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {},
+   "execution_count": 3,
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Sex               0\n",
-      "Length            0\n",
-      "Diameter          0\n",
-      "Height            0\n",
-      "Weight            0\n",
-      "Shucked Weight    0\n",
-      "Viscera Weight    0\n",
-      "Shell Weight      0\n",
-      "Age               0\n",
-      "dtype: int64\n"
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 3893 entries, 0 to 3892\n",
+      "Data columns (total 9 columns):\n",
+      " #   Column          Non-Null Count  Dtype  \n",
+      "---  ------          --------------  -----  \n",
+      " 0   Sex             3893 non-null   object \n",
+      " 1   Length          3893 non-null   float64\n",
+      " 2   Diameter        3893 non-null   float64\n",
+      " 3   Height          3893 non-null   float64\n",
+      " 4   Weight          3893 non-null   float64\n",
+      " 5   Shucked Weight  3893 non-null   float64\n",
+      " 6   Viscera Weight  3893 non-null   float64\n",
+      " 7   Shell Weight    3893 non-null   float64\n",
+      " 8   Age             3893 non-null   int64  \n",
+      "dtypes: float64(7), int64(1), object(1)\n",
+      "memory usage: 273.9+ KB\n"
      ]
     }
    ],
    "source": [
-    "sum_nan = data.isnull().sum()\n",
-    "print(sum_nan)"
+    "data.info()"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "No hay valores nulos"
+    "Cantidad de Registros y Tipos de Variables:\n",
+    "\n",
+    "> Tenemos `3893` registros, en cada una de las `9` variables obtenidas.\n",
+    "\n",
+    "> Todas las variables son tipo númerico en particular `Float`, excepto Sex que es de tipo `categórico`.\n",
+    "\n",
+    "> En particular, la variable númerica `Age` es discreta, excepto las otras variables númericas que son continuas."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
@@ -552,7 +392,7 @@
        "max         21.545620     28.491248    29.000000  "
       ]
      },
-     "execution_count": 10,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -565,12 +405,40 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "!que vemos!🤔 "
+    "> Note que el dataset no tiene `valores faltantes`, cada columna tiene `3893` registros completos."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Sex               0\n",
+      "Length            0\n",
+      "Diameter          0\n",
+      "Height            0\n",
+      "Weight            0\n",
+      "Shucked Weight    0\n",
+      "Viscera Weight    0\n",
+      "Shell Weight      0\n",
+      "Age               0\n",
+      "dtype: int64\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Para mostrar más detalle del dataset, no es necesario\n",
+    "sum_nan = data.isnull().sum()\n",
+    "print(sum_nan)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -595,170 +463,91 @@
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>Sex</th>\n",
+       "      <th>Length</th>\n",
+       "      <th>Diameter</th>\n",
+       "      <th>Height</th>\n",
+       "      <th>Weight</th>\n",
+       "      <th>Shucked Weight</th>\n",
+       "      <th>Viscera Weight</th>\n",
+       "      <th>Shell Weight</th>\n",
+       "      <th>Age</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>count</th>\n",
-       "      <td>3893</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>unique</th>\n",
-       "      <td>3</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>top</th>\n",
-       "      <td>M</td>\n",
+       "      <th>269</th>\n",
+       "      <td>I</td>\n",
+       "      <td>0.7875</td>\n",
+       "      <td>0.575</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>3.798833</td>\n",
+       "      <td>1.630096</td>\n",
+       "      <td>0.807961</td>\n",
+       "      <td>9.936500</td>\n",
+       "      <td>6</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>freq</th>\n",
-       "      <td>1435</td>\n",
+       "      <th>3867</th>\n",
+       "      <td>I</td>\n",
+       "      <td>1.0750</td>\n",
+       "      <td>0.850</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>12.133586</td>\n",
+       "      <td>5.854172</td>\n",
+       "      <td>2.438057</td>\n",
+       "      <td>3.260193</td>\n",
+       "      <td>8</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
-       "         Sex\n",
-       "count   3893\n",
-       "unique     3\n",
-       "top        M\n",
-       "freq    1435"
+       "     Sex  Length  Diameter  Height     Weight  Shucked Weight  Viscera Weight  \\\n",
+       "269    I  0.7875     0.575     0.0   3.798833        1.630096        0.807961   \n",
+       "3867   I  1.0750     0.850     0.0  12.133586        5.854172        2.438057   \n",
+       "\n",
+       "      Shell Weight  Age  \n",
+       "269       9.936500    6  \n",
+       "3867      3.260193    8  "
       ]
      },
-     "execution_count": 11,
+     "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "data.describe(include = object)"
+    "data[data[\"Height\"] == 0]"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 12,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "M    1435\n",
-       "I    1233\n",
-       "F    1225\n",
-       "Name: Sex, dtype: int64"
-      ]
-     },
-     "execution_count": 12,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "data[\"Sex\"].value_counts()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Notemos que hay más cangrejos de sexo masculino"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 13,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<AxesSubplot:>"
-      ]
-     },
-     "execution_count": 13,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "# Mostrar los valores de la caracteristica con un histograma\n",
-    "%matplotlib inline\n",
-    "data[\"Sex\"].hist()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 14,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<function matplotlib.pyplot.show(close=None, block=None)>"
-      ]
-     },
-     "execution_count": 14,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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-      "text/plain": [
-       "<Figure size 1500x1000 with 9 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "data.hist(bins = 30 ,  figsize=(15, 10))\n",
-    "plt.show"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": []
-  },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Vamos a analizar la correlación entre los atributos"
+    "> Note que la columna `Height` su valor minimo es cero, lo cual no tiene sentido en nuestros datos."
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "#Primero: Transformamos los valores del atributo sex de categoricos a númericos"
+    "# Imputación de datos "
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
-    "from sklearn.preprocessing import LabelEncoder"
+    "data.iloc[269, 3] = 0.180317\n",
+    "data.iloc[3867, 3] = 0.170518"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
@@ -794,246 +583,101 @@
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>0</td>\n",
-       "      <td>1.4375</td>\n",
-       "      <td>1.1750</td>\n",
-       "      <td>0.4125</td>\n",
-       "      <td>24.635715</td>\n",
-       "      <td>12.332033</td>\n",
-       "      <td>5.584852</td>\n",
-       "      <td>6.747181</td>\n",
-       "      <td>9</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>2</td>\n",
-       "      <td>0.8875</td>\n",
-       "      <td>0.6500</td>\n",
-       "      <td>0.2125</td>\n",
-       "      <td>5.400580</td>\n",
-       "      <td>2.296310</td>\n",
-       "      <td>1.374951</td>\n",
-       "      <td>1.559222</td>\n",
-       "      <td>6</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>1</td>\n",
-       "      <td>1.0375</td>\n",
-       "      <td>0.7750</td>\n",
-       "      <td>0.2500</td>\n",
-       "      <td>7.952035</td>\n",
-       "      <td>3.231843</td>\n",
-       "      <td>1.601747</td>\n",
-       "      <td>2.764076</td>\n",
-       "      <td>6</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>0</td>\n",
-       "      <td>1.1750</td>\n",
-       "      <td>0.8875</td>\n",
-       "      <td>0.2500</td>\n",
-       "      <td>13.480187</td>\n",
-       "      <td>4.748541</td>\n",
-       "      <td>2.282135</td>\n",
-       "      <td>5.244657</td>\n",
-       "      <td>10</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>1</td>\n",
-       "      <td>0.8875</td>\n",
-       "      <td>0.6625</td>\n",
-       "      <td>0.2125</td>\n",
-       "      <td>6.903103</td>\n",
-       "      <td>3.458639</td>\n",
-       "      <td>1.488349</td>\n",
-       "      <td>1.700970</td>\n",
-       "      <td>6</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",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3888</th>\n",
-       "      <td>0</td>\n",
-       "      <td>1.4625</td>\n",
-       "      <td>1.1375</td>\n",
-       "      <td>0.3250</td>\n",
-       "      <td>24.819987</td>\n",
-       "      <td>11.651644</td>\n",
-       "      <td>5.854172</td>\n",
-       "      <td>6.378637</td>\n",
-       "      <td>8</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3889</th>\n",
-       "      <td>0</td>\n",
-       "      <td>1.5500</td>\n",
-       "      <td>1.2125</td>\n",
-       "      <td>0.4375</td>\n",
-       "      <td>34.458817</td>\n",
-       "      <td>15.450477</td>\n",
-       "      <td>7.172423</td>\n",
-       "      <td>9.780577</td>\n",
-       "      <td>10</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3890</th>\n",
-       "      <td>1</td>\n",
-       "      <td>0.6250</td>\n",
-       "      <td>0.4625</td>\n",
-       "      <td>0.1625</td>\n",
-       "      <td>2.012815</td>\n",
-       "      <td>0.765436</td>\n",
-       "      <td>0.524466</td>\n",
-       "      <td>0.637864</td>\n",
-       "      <td>5</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3891</th>\n",
-       "      <td>1</td>\n",
-       "      <td>1.0625</td>\n",
-       "      <td>0.7750</td>\n",
-       "      <td>0.2625</td>\n",
-       "      <td>10.347568</td>\n",
-       "      <td>4.507570</td>\n",
-       "      <td>2.338834</td>\n",
-       "      <td>2.976698</td>\n",
-       "      <td>6</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3892</th>\n",
-       "      <td>1</td>\n",
-       "      <td>0.7875</td>\n",
-       "      <td>0.6125</td>\n",
-       "      <td>0.2125</td>\n",
-       "      <td>4.068153</td>\n",
-       "      <td>1.502523</td>\n",
-       "      <td>1.346601</td>\n",
-       "      <td>1.417475</td>\n",
-       "      <td>8</td>\n",
-       "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>3893 rows × 9 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "      Sex  Length  Diameter  Height     Weight  Shucked Weight  \\\n",
-       "0       0  1.4375    1.1750  0.4125  24.635715       12.332033   \n",
-       "1       2  0.8875    0.6500  0.2125   5.400580        2.296310   \n",
-       "2       1  1.0375    0.7750  0.2500   7.952035        3.231843   \n",
-       "3       0  1.1750    0.8875  0.2500  13.480187        4.748541   \n",
-       "4       1  0.8875    0.6625  0.2125   6.903103        3.458639   \n",
-       "...   ...     ...       ...     ...        ...             ...   \n",
-       "3888    0  1.4625    1.1375  0.3250  24.819987       11.651644   \n",
-       "3889    0  1.5500    1.2125  0.4375  34.458817       15.450477   \n",
-       "3890    1  0.6250    0.4625  0.1625   2.012815        0.765436   \n",
-       "3891    1  1.0625    0.7750  0.2625  10.347568        4.507570   \n",
-       "3892    1  0.7875    0.6125  0.2125   4.068153        1.502523   \n",
-       "\n",
-       "      Viscera Weight  Shell Weight  Age  \n",
-       "0           5.584852      6.747181    9  \n",
-       "1           1.374951      1.559222    6  \n",
-       "2           1.601747      2.764076    6  \n",
-       "3           2.282135      5.244657   10  \n",
-       "4           1.488349      1.700970    6  \n",
-       "...              ...           ...  ...  \n",
-       "3888        5.854172      6.378637    8  \n",
-       "3889        7.172423      9.780577   10  \n",
-       "3890        0.524466      0.637864    5  \n",
-       "3891        2.338834      2.976698    6  \n",
-       "3892        1.346601      1.417475    8  \n",
-       "\n",
-       "[3893 rows x 9 columns]"
+       "Empty DataFrame\n",
+       "Columns: [Sex, Length, Diameter, Height, Weight, Shucked Weight, Viscera Weight, Shell Weight, Age]\n",
+       "Index: []"
       ]
      },
-     "execution_count": 17,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "labelencoder = LabelEncoder()\n",
-    "data[\"Sex\"] = labelencoder.fit_transform(data[\"Sex\"])\n",
-    "data"
+    "data[data[\"Height\"] == 0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0\n"
+     ]
+    }
+   ],
+   "source": [
+    "sum_duplicados = data.duplicated().sum()\n",
+    "print(sum_duplicados)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "#### Note que: \n",
-    " - 0 => Femenino\n",
-    " - 1 => Indeterminado\n",
-    " - 2 => Masculino\n"
+    "> No tenemos registros `duplicados`"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Construimos la matriz de correlación"
+    "# **Estadísticas Descriptivas**\n",
+    "\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "Age               1.000000\n",
-       "Shell Weight      0.625195\n",
-       "Diameter          0.573844\n",
-       "Length            0.554973\n",
-       "Height            0.551956\n",
-       "Weight            0.538819\n",
-       "Viscera Weight    0.501328\n",
-       "Shucked Weight    0.418760\n",
-       "Sex              -0.033700\n",
-       "Name: Age, dtype: float64"
+       "<function matplotlib.pyplot.show(close=None, block=None)>"
       ]
      },
-     "execution_count": 18,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1500x1000 with 9 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     }
    ],
    "source": [
-    "corr_matrix = data.corr()\n",
-    "corr_matrix[\"Age\"].sort_values(ascending = False)"
+    "data.hist(bins = 30, color = \"Skyblue\",  figsize=(15, 10))\n",
+    "plt.show"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Note que las caracteristicas que tienen más correlación con Age son:\n",
-    " - Shell Weight\n",
-    " - Diameter\n",
-    " - Length\n",
-    " - Height\n",
-    " - Weight\n"
+    "# Variables categóricas\n",
+    "\n",
+    "> Solo tenemos una variable categórica que corresponde a `Sex`"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
@@ -1058,200 +702,63 @@
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>Sex</th>\n",
-       "      <th>Length</th>\n",
-       "      <th>Diameter</th>\n",
-       "      <th>Height</th>\n",
-       "      <th>Weight</th>\n",
-       "      <th>Shucked Weight</th>\n",
-       "      <th>Viscera Weight</th>\n",
-       "      <th>Shell Weight</th>\n",
-       "      <th>Age</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>Sex</th>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>-0.034975</td>\n",
-       "      <td>-0.038394</td>\n",
-       "      <td>-0.041629</td>\n",
-       "      <td>-0.021773</td>\n",
-       "      <td>-0.002353</td>\n",
-       "      <td>-0.032110</td>\n",
-       "      <td>-0.036216</td>\n",
-       "      <td>-0.033700</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>Length</th>\n",
-       "      <td>-0.034975</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.986653</td>\n",
-       "      <td>0.823081</td>\n",
-       "      <td>0.925374</td>\n",
-       "      <td>0.898181</td>\n",
-       "      <td>0.903253</td>\n",
-       "      <td>0.897736</td>\n",
-       "      <td>0.554973</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>Diameter</th>\n",
-       "      <td>-0.038394</td>\n",
-       "      <td>0.986653</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.829532</td>\n",
-       "      <td>0.925770</td>\n",
-       "      <td>0.893626</td>\n",
-       "      <td>0.899810</td>\n",
-       "      <td>0.905561</td>\n",
-       "      <td>0.573844</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>Height</th>\n",
-       "      <td>-0.041629</td>\n",
-       "      <td>0.823081</td>\n",
-       "      <td>0.829532</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.814405</td>\n",
-       "      <td>0.770961</td>\n",
-       "      <td>0.793272</td>\n",
-       "      <td>0.812290</td>\n",
-       "      <td>0.551956</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>Weight</th>\n",
-       "      <td>-0.021773</td>\n",
-       "      <td>0.925374</td>\n",
-       "      <td>0.925770</td>\n",
-       "      <td>0.814405</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.969077</td>\n",
-       "      <td>0.965583</td>\n",
-       "      <td>0.955269</td>\n",
-       "      <td>0.538819</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>Shucked Weight</th>\n",
-       "      <td>-0.002353</td>\n",
-       "      <td>0.898181</td>\n",
-       "      <td>0.893626</td>\n",
-       "      <td>0.770961</td>\n",
-       "      <td>0.969077</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.931280</td>\n",
-       "      <td>0.882406</td>\n",
-       "      <td>0.418760</td>\n",
+       "      <th>count</th>\n",
+       "      <td>3893</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>Viscera Weight</th>\n",
-       "      <td>-0.032110</td>\n",
-       "      <td>0.903253</td>\n",
-       "      <td>0.899810</td>\n",
-       "      <td>0.793272</td>\n",
-       "      <td>0.965583</td>\n",
-       "      <td>0.931280</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.906105</td>\n",
-       "      <td>0.501328</td>\n",
+       "      <th>unique</th>\n",
+       "      <td>3</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>Shell Weight</th>\n",
-       "      <td>-0.036216</td>\n",
-       "      <td>0.897736</td>\n",
-       "      <td>0.905561</td>\n",
-       "      <td>0.812290</td>\n",
-       "      <td>0.955269</td>\n",
-       "      <td>0.882406</td>\n",
-       "      <td>0.906105</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.625195</td>\n",
+       "      <th>top</th>\n",
+       "      <td>M</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>Age</th>\n",
-       "      <td>-0.033700</td>\n",
-       "      <td>0.554973</td>\n",
-       "      <td>0.573844</td>\n",
-       "      <td>0.551956</td>\n",
-       "      <td>0.538819</td>\n",
-       "      <td>0.418760</td>\n",
-       "      <td>0.501328</td>\n",
-       "      <td>0.625195</td>\n",
-       "      <td>1.000000</td>\n",
+       "      <th>freq</th>\n",
+       "      <td>1435</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
-       "                     Sex    Length  Diameter    Height    Weight  \\\n",
-       "Sex             1.000000 -0.034975 -0.038394 -0.041629 -0.021773   \n",
-       "Length         -0.034975  1.000000  0.986653  0.823081  0.925374   \n",
-       "Diameter       -0.038394  0.986653  1.000000  0.829532  0.925770   \n",
-       "Height         -0.041629  0.823081  0.829532  1.000000  0.814405   \n",
-       "Weight         -0.021773  0.925374  0.925770  0.814405  1.000000   \n",
-       "Shucked Weight -0.002353  0.898181  0.893626  0.770961  0.969077   \n",
-       "Viscera Weight -0.032110  0.903253  0.899810  0.793272  0.965583   \n",
-       "Shell Weight   -0.036216  0.897736  0.905561  0.812290  0.955269   \n",
-       "Age            -0.033700  0.554973  0.573844  0.551956  0.538819   \n",
-       "\n",
-       "                Shucked Weight  Viscera Weight  Shell Weight       Age  \n",
-       "Sex                  -0.002353       -0.032110     -0.036216 -0.033700  \n",
-       "Length                0.898181        0.903253      0.897736  0.554973  \n",
-       "Diameter              0.893626        0.899810      0.905561  0.573844  \n",
-       "Height                0.770961        0.793272      0.812290  0.551956  \n",
-       "Weight                0.969077        0.965583      0.955269  0.538819  \n",
-       "Shucked Weight        1.000000        0.931280      0.882406  0.418760  \n",
-       "Viscera Weight        0.931280        1.000000      0.906105  0.501328  \n",
-       "Shell Weight          0.882406        0.906105      1.000000  0.625195  \n",
-       "Age                   0.418760        0.501328      0.625195  1.000000  "
+       "         Sex\n",
+       "count   3893\n",
+       "unique     3\n",
+       "top        M\n",
+       "freq    1435"
       ]
      },
-     "execution_count": 21,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "#Mostrar correlación lineal entre todos los atributos del conjunto de datos\n",
-    "data.corr()"
+    "data.describe(include = object)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Mostremos las diferentes cantidades de cada tipo de sexo en cangrejos"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
      "data": {
+      "image/png": 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",
       "text/plain": [
-       "([<matplotlib.axis.YTick at 0x248eb86fdf0>,\n",
-       "  <matplotlib.axis.YTick at 0x248eb86f670>,\n",
-       "  <matplotlib.axis.YTick at 0x248eb5befd0>,\n",
-       "  <matplotlib.axis.YTick at 0x248eb8b17c0>,\n",
-       "  <matplotlib.axis.YTick at 0x248eb8b50a0>,\n",
-       "  <matplotlib.axis.YTick at 0x248eb8b17f0>,\n",
-       "  <matplotlib.axis.YTick at 0x248eb8a2ee0>,\n",
-       "  <matplotlib.axis.YTick at 0x248eb8b5490>,\n",
-       "  <matplotlib.axis.YTick at 0x248eb8b5be0>],\n",
-       " [Text(0, 0, 'Sex'),\n",
-       "  Text(0, 1, 'Length'),\n",
-       "  Text(0, 2, 'Diameter'),\n",
-       "  Text(0, 3, 'Height'),\n",
-       "  Text(0, 4, 'Weight'),\n",
-       "  Text(0, 5, 'Shucked Weight'),\n",
-       "  Text(0, 6, 'Viscera Weight'),\n",
-       "  Text(0, 7, 'Shell Weight'),\n",
-       "  Text(0, 8, 'Age')])"
-      ]
-     },
-     "execution_count": 23,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 800x800 with 1 Axes>"
+       "<Figure size 640x480 with 1 Axes>"
       ]
      },
      "metadata": {},
@@ -1259,178 +766,5338 @@
     }
    ],
    "source": [
-    "#Representar gráficamente la matriz de correlación\n",
-    "corr = data.corr()\n",
-    "fig, ax = plt.subplots(figsize=(8, 8))\n",
-    "ax.matshow(corr)\n",
-    "plt.xticks(range(len(corr.columns)), corr.columns)\n",
-    "plt.yticks(range(len(corr.columns)), corr.columns)"
+    "from collections import Counter # para que nos obtenga las distintas catergorias y el número total de cada una\n",
+    "\n",
+    "\n",
+    "counts = Counter(data[\"Sex\"]) # Nos devuelve un diccionario\n",
+    "categories  = list(counts.keys())\n",
+    "frequencies = list(counts.values())\n",
+    "\n",
+    "plt.bar(categories, frequencies, color = \"Skyblue\", edgecolor = \"black\")\n",
+    "\n",
+    "for i, freq in enumerate(frequencies):\n",
+    "    plt.text(i, freq + 0.2, str(freq), ha = \"center\", va = \"bottom\")\n",
+    "\n",
+    "\n",
+    "plt.title(\"Frecuencia de cada Sexo\")\n",
+    "plt.xlabel(\"Categorías\")\n",
+    "plt.ylabel(\"Frecuencia\")\n",
+    "\n",
+    "plt.show()\n"
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": 24,
+   "cell_type": "markdown",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 1200x800 with 36 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
    "source": [
-    "# Representar gráficamente las correlaciones\n",
-    "from pandas.plotting import scatter_matrix\n",
-    "\n",
-    "atributos = [\"Shell Weight\", \"Diameter\", \"Length\", \"Height\", \"Weight\", \"Age\"]\n",
+    "> Notemos que hay más cangrejos de sexo masculino.\n",
     "\n",
-    "scatter_matrix(data[atributos], figsize = (12, 8))\n",
-    "plt.show()"
+    "> En cambio en femenino e indeterminado tenemos aproxidamente la misma proporción."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Análisis y Tratamiento de Valores Atípicos"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import plotly.express as px"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "text/plain": [
-       "<AxesSubplot:>"
-      ]
-     },
-     "execution_count": 27,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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+            "linecolor": "white",
+            "ticks": ""
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+           "bgcolor": "#E5ECF6",
+           "caxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           }
+          },
+          "title": {
+           "x": 0.05
+          },
+          "xaxis": {
+           "automargin": true,
+           "gridcolor": "white",
+           "linecolor": "white",
+           "ticks": "",
+           "title": {
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+           "zerolinecolor": "white",
+           "zerolinewidth": 2
+          },
+          "yaxis": {
+           "automargin": true,
+           "gridcolor": "white",
+           "linecolor": "white",
+           "ticks": "",
+           "title": {
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+           "zerolinewidth": 2
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+        "xaxis": {
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+          1
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+        },
+        "yaxis": {
+         "anchor": "x",
+         "domain": [
+          0,
+          1
+         ],
+         "title": {
+          "text": "Age"
+         }
+        }
+       }
+      }
      },
      "metadata": {},
      "output_type": "display_data"
     }
    ],
    "source": [
-    "sns.heatmap(data.corr(), annot = True )"
+    "fig = px.box(data[\"Age\"], y = \"Age\", width= 600, height= 600)\n",
+    "fig.show()"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Vamos a comparar Age con la distintas caracteristicas presentes en el dataset"
+    "> Necesitamos quitar o recortar los valores atipicos o extremos, ya que es un pre-requesito para aplicar una regresión lineal.\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
     {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 800x800 with 7 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Tenemos 257 valores extremos.\n"
+     ]
     }
    ],
    "source": [
-    "fig, axis = plt.subplots(3, 3, figsize = (8, 8))\n",
+    "# Calculos\n",
+    "Q1 = np.percentile(data[\"Age\"], 25)\n",
+    "Q3 = np.percentile(data[\"Age\"], 75)\n",
+    "IQR = Q3 - Q1\n",
     "\n",
-    "#Crear un diagrama de dispersión multiple\n",
-    "sns.regplot(ax = axis[0,0], data = data, x = \"Sex\", y = \"Age\")\n",
-    "sns.regplot(ax = axis[0,1], data = data, x = \"Length\", y = \"Age\").set(ylabel = None)\n",
-    "sns.regplot(ax = axis[0,2], data = data , x = \"Diameter\", y = \"Age\").set(ylabel = None)\n",
-    "sns.regplot(ax = axis[1,0], data = data, x = \"Weight\", y = \"Age\")\n",
-    "sns.regplot(ax = axis[1,1], data = data, x = \"Shucked Weight\", y = \"Age\").set(ylabel = None)\n",
-    "sns.regplot(ax = axis[1,2], data = data, x = \"Viscera Weight\", y = \"Age\").set(ylabel = None)\n",
-    "sns.regplot(ax = axis[2,0], data = data, x = \"Shell Weight\", y = \"Age\")\n",
+    "# Limites\n",
+    "lower_limit = Q1 - 1.5 * IQR\n",
+    "upper_limit = Q3 + 1.5 * IQR\n",
     "\n",
-    "#Ajustar el layout\n",
-    "plt.tight_layout()\n",
-    "plt.delaxes(axis[2,1])\n",
-    "plt.delaxes(axis[2,2])\n",
+    "# Identificar valores extremos\n",
+    "outliers_age = [x for x in data.Age if x < lower_limit or x > upper_limit]\n",
+    "#print(\"Valores extremos:\", outliers_age)\n",
     "\n",
-    "#Mostrar el plot\n",
-    "plt.show()"
+    "print(\"Tenemos\", len(outliers_age), \"valores extremos.\")"
    ]
   },
   {
-   "cell_type": "markdown",
+   "cell_type": "code",
+   "execution_count": 16,
    "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "3636\n"
+     ]
+    }
+   ],
    "source": [
-    "# Preparacion de Datos"
+    "filtered_age = [x for x in data[\"Age\"] if lower_limit <= x and x <= upper_limit]\n",
+    "print(len(filtered_age))"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "markdown",
+   "execution_count": 17,
    "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>Sex</th>\n",
+       "      <th>Length</th>\n",
+       "      <th>Diameter</th>\n",
+       "      <th>Height</th>\n",
+       "      <th>Weight</th>\n",
+       "      <th>Shucked Weight</th>\n",
+       "      <th>Viscera Weight</th>\n",
+       "      <th>Shell Weight</th>\n",
+       "      <th>Age</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>I</td>\n",
+       "      <td>0.9125</td>\n",
+       "      <td>0.6875</td>\n",
+       "      <td>0.3375</td>\n",
+       "      <td>6.803880</td>\n",
+       "      <td>3.061746</td>\n",
+       "      <td>1.261553</td>\n",
+       "      <td>2.083688</td>\n",
+       "      <td>7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>F</td>\n",
+       "      <td>1.3000</td>\n",
+       "      <td>1.0000</td>\n",
+       "      <td>0.3250</td>\n",
+       "      <td>17.704263</td>\n",
+       "      <td>6.095142</td>\n",
+       "      <td>5.854172</td>\n",
+       "      <td>4.819415</td>\n",
+       "      <td>15</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>F</td>\n",
+       "      <td>1.3000</td>\n",
+       "      <td>1.0000</td>\n",
+       "      <td>0.3250</td>\n",
+       "      <td>17.704263</td>\n",
+       "      <td>6.095142</td>\n",
+       "      <td>5.854172</td>\n",
+       "      <td>4.819415</td>\n",
+       "      <td>15</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>M</td>\n",
+       "      <td>0.8250</td>\n",
+       "      <td>0.5375</td>\n",
+       "      <td>0.1875</td>\n",
+       "      <td>3.246018</td>\n",
+       "      <td>1.275727</td>\n",
+       "      <td>0.751262</td>\n",
+       "      <td>0.992232</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>F</td>\n",
+       "      <td>1.3000</td>\n",
+       "      <td>1.0000</td>\n",
+       "      <td>0.3250</td>\n",
+       "      <td>17.704263</td>\n",
+       "      <td>6.095142</td>\n",
+       "      <td>5.854172</td>\n",
+       "      <td>4.819415</td>\n",
+       "      <td>15</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Sex  Length  Diameter  Height     Weight  Shucked Weight  Viscera Weight  \\\n",
+       "9    I  0.9125    0.6875  0.3375   6.803880        3.061746        1.261553   \n",
+       "6    F  1.3000    1.0000  0.3250  17.704263        6.095142        5.854172   \n",
+       "6    F  1.3000    1.0000  0.3250  17.704263        6.095142        5.854172   \n",
+       "10   M  0.8250    0.5375  0.1875   3.246018        1.275727        0.751262   \n",
+       "6    F  1.3000    1.0000  0.3250  17.704263        6.095142        5.854172   \n",
+       "\n",
+       "    Shell Weight  Age  \n",
+       "9       2.083688    7  \n",
+       "6       4.819415   15  \n",
+       "6       4.819415   15  \n",
+       "10      0.992232    6  \n",
+       "6       4.819415   15  "
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# Modelado"
+    "df_clear = data.iloc[filtered_age]\n",
+    "df_clear.head()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 20,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "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>Sex</th>\n",
+       "      <th>Length</th>\n",
+       "      <th>Diameter</th>\n",
+       "      <th>Height</th>\n",
+       "      <th>Weight</th>\n",
+       "      <th>Shucked Weight</th>\n",
+       "      <th>Viscera Weight</th>\n",
+       "      <th>Shell Weight</th>\n",
+       "      <th>Age</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>I</td>\n",
+       "      <td>0.9125</td>\n",
+       "      <td>0.6875</td>\n",
+       "      <td>0.3375</td>\n",
+       "      <td>6.803880</td>\n",
+       "      <td>3.061746</td>\n",
+       "      <td>1.261553</td>\n",
+       "      <td>2.083688</td>\n",
+       "      <td>7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>F</td>\n",
+       "      <td>1.3000</td>\n",
+       "      <td>1.0000</td>\n",
+       "      <td>0.3250</td>\n",
+       "      <td>17.704263</td>\n",
+       "      <td>6.095142</td>\n",
+       "      <td>5.854172</td>\n",
+       "      <td>4.819415</td>\n",
+       "      <td>15</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>F</td>\n",
+       "      <td>1.3000</td>\n",
+       "      <td>1.0000</td>\n",
+       "      <td>0.3250</td>\n",
+       "      <td>17.704263</td>\n",
+       "      <td>6.095142</td>\n",
+       "      <td>5.854172</td>\n",
+       "      <td>4.819415</td>\n",
+       "      <td>15</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>M</td>\n",
+       "      <td>0.8250</td>\n",
+       "      <td>0.5375</td>\n",
+       "      <td>0.1875</td>\n",
+       "      <td>3.246018</td>\n",
+       "      <td>1.275727</td>\n",
+       "      <td>0.751262</td>\n",
+       "      <td>0.992232</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>F</td>\n",
+       "      <td>1.3000</td>\n",
+       "      <td>1.0000</td>\n",
+       "      <td>0.3250</td>\n",
+       "      <td>17.704263</td>\n",
+       "      <td>6.095142</td>\n",
+       "      <td>5.854172</td>\n",
+       "      <td>4.819415</td>\n",
+       "      <td>15</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  Sex  Length  Diameter  Height     Weight  Shucked Weight  Viscera Weight  \\\n",
+       "0   I  0.9125    0.6875  0.3375   6.803880        3.061746        1.261553   \n",
+       "1   F  1.3000    1.0000  0.3250  17.704263        6.095142        5.854172   \n",
+       "2   F  1.3000    1.0000  0.3250  17.704263        6.095142        5.854172   \n",
+       "3   M  0.8250    0.5375  0.1875   3.246018        1.275727        0.751262   \n",
+       "4   F  1.3000    1.0000  0.3250  17.704263        6.095142        5.854172   \n",
+       "\n",
+       "   Shell Weight  Age  \n",
+       "0      2.083688    7  \n",
+       "1      4.819415   15  \n",
+       "2      4.819415   15  \n",
+       "3      0.992232    6  \n",
+       "4      4.819415   15  "
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Tenemos que reiniciar los index de df_clear\n",
+    "df_clear.reset_index(drop = True, inplace = True)\n",
+    "df_clear.head()"
+   ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
+   "metadata": {},
    "source": [
-    "# Validación"
+    "# Correlaciones"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 21,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Axes: >"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "df_clear_copy = df_clear.drop(columns=[\"Sex\"])\n",
+    "sns.heatmap(df_clear_copy.corr(method=\"pearson\"), annot = True ) # por defecto el metodo de corr() es pearson"
+   ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
+   "metadata": {},
    "source": [
-    "# Despliegue"
+    "Note que las variables que tienen más correlación con nuestra variable objetivo `Age` son:\n",
+    "\n",
+    "        • Viscera Weight\n",
+    "        • Diameter\n",
+    "        • Lenght\n",
+    "        • Weight\n",
+    "        • Shell Weight\n",
+    "        • Shucked Weight\n",
+    "\n",
+    "Note que hay variables que tienen una correlación muy alta respecto a las otras variables, por ejemplo algunas son:\n",
+    "\n",
+    "        • length\n",
+    "        • Diameter\n",
+    "\n",
+    "Al que estas varibles tenga una correlación tan cercana o igual a `1` (una correlación positiva), nos indica que entre más aumente una variable la otra tambien va a crecer ya que tienen una correlación alta. Ejemplo, entre más diametro tenga va a ser más largo el cangrejo.\n",
+    "\n",
+    "\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 22,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "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>Sex</th>\n",
+       "      <th>Length</th>\n",
+       "      <th>Diameter</th>\n",
+       "      <th>Height</th>\n",
+       "      <th>Weight</th>\n",
+       "      <th>Shucked Weight</th>\n",
+       "      <th>Viscera Weight</th>\n",
+       "      <th>Shell Weight</th>\n",
+       "      <th>Age</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>I</td>\n",
+       "      <td>0.9125</td>\n",
+       "      <td>0.6875</td>\n",
+       "      <td>0.3375</td>\n",
+       "      <td>6.803880</td>\n",
+       "      <td>3.061746</td>\n",
+       "      <td>1.261553</td>\n",
+       "      <td>2.083688</td>\n",
+       "      <td>7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>F</td>\n",
+       "      <td>1.3000</td>\n",
+       "      <td>1.0000</td>\n",
+       "      <td>0.3250</td>\n",
+       "      <td>17.704263</td>\n",
+       "      <td>6.095142</td>\n",
+       "      <td>5.854172</td>\n",
+       "      <td>4.819415</td>\n",
+       "      <td>15</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>F</td>\n",
+       "      <td>1.3000</td>\n",
+       "      <td>1.0000</td>\n",
+       "      <td>0.3250</td>\n",
+       "      <td>17.704263</td>\n",
+       "      <td>6.095142</td>\n",
+       "      <td>5.854172</td>\n",
+       "      <td>4.819415</td>\n",
+       "      <td>15</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>M</td>\n",
+       "      <td>0.8250</td>\n",
+       "      <td>0.5375</td>\n",
+       "      <td>0.1875</td>\n",
+       "      <td>3.246018</td>\n",
+       "      <td>1.275727</td>\n",
+       "      <td>0.751262</td>\n",
+       "      <td>0.992232</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>F</td>\n",
+       "      <td>1.3000</td>\n",
+       "      <td>1.0000</td>\n",
+       "      <td>0.3250</td>\n",
+       "      <td>17.704263</td>\n",
+       "      <td>6.095142</td>\n",
+       "      <td>5.854172</td>\n",
+       "      <td>4.819415</td>\n",
+       "      <td>15</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  Sex  Length  Diameter  Height     Weight  Shucked Weight  Viscera Weight  \\\n",
+       "0   I  0.9125    0.6875  0.3375   6.803880        3.061746        1.261553   \n",
+       "1   F  1.3000    1.0000  0.3250  17.704263        6.095142        5.854172   \n",
+       "2   F  1.3000    1.0000  0.3250  17.704263        6.095142        5.854172   \n",
+       "3   M  0.8250    0.5375  0.1875   3.246018        1.275727        0.751262   \n",
+       "4   F  1.3000    1.0000  0.3250  17.704263        6.095142        5.854172   \n",
+       "\n",
+       "   Shell Weight  Age  \n",
+       "0      2.083688    7  \n",
+       "1      4.819415   15  \n",
+       "2      4.819415   15  \n",
+       "3      0.992232    6  \n",
+       "4      4.819415   15  "
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Guardamos el dataset limpio\n",
+    "df_clear.to_csv(\"D:/DataSets/CrabAge/data_clear.csv\")\n",
+    "df_clear.head()"
+   ]
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "Sanchez",
    "language": "python",
    "name": "python3"
   },
@@ -1444,7 +6111,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.4"
+   "version": "3.11.1"
   }
  },
  "nbformat": 4,
diff --git a/Notebooks/modelado.ipynb b/Notebooks/modelado.ipynb
new file mode 100644
index 0000000..59cab1f
--- /dev/null
+++ b/Notebooks/modelado.ipynb
@@ -0,0 +1,1601 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# **Carga de Datos**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "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>Sex</th>\n",
+       "      <th>Length</th>\n",
+       "      <th>Diameter</th>\n",
+       "      <th>Height</th>\n",
+       "      <th>Weight</th>\n",
+       "      <th>Shucked Weight</th>\n",
+       "      <th>Viscera Weight</th>\n",
+       "      <th>Shell Weight</th>\n",
+       "      <th>Age</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>I</td>\n",
+       "      <td>0.9125</td>\n",
+       "      <td>0.6875</td>\n",
+       "      <td>0.3375</td>\n",
+       "      <td>6.803880</td>\n",
+       "      <td>3.061746</td>\n",
+       "      <td>1.261553</td>\n",
+       "      <td>2.083688</td>\n",
+       "      <td>7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>F</td>\n",
+       "      <td>1.3000</td>\n",
+       "      <td>1.0000</td>\n",
+       "      <td>0.3250</td>\n",
+       "      <td>17.704263</td>\n",
+       "      <td>6.095142</td>\n",
+       "      <td>5.854172</td>\n",
+       "      <td>4.819415</td>\n",
+       "      <td>15</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>F</td>\n",
+       "      <td>1.3000</td>\n",
+       "      <td>1.0000</td>\n",
+       "      <td>0.3250</td>\n",
+       "      <td>17.704263</td>\n",
+       "      <td>6.095142</td>\n",
+       "      <td>5.854172</td>\n",
+       "      <td>4.819415</td>\n",
+       "      <td>15</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>M</td>\n",
+       "      <td>0.8250</td>\n",
+       "      <td>0.5375</td>\n",
+       "      <td>0.1875</td>\n",
+       "      <td>3.246018</td>\n",
+       "      <td>1.275727</td>\n",
+       "      <td>0.751262</td>\n",
+       "      <td>0.992232</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>F</td>\n",
+       "      <td>1.3000</td>\n",
+       "      <td>1.0000</td>\n",
+       "      <td>0.3250</td>\n",
+       "      <td>17.704263</td>\n",
+       "      <td>6.095142</td>\n",
+       "      <td>5.854172</td>\n",
+       "      <td>4.819415</td>\n",
+       "      <td>15</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  Sex  Length  Diameter  Height     Weight  Shucked Weight  Viscera Weight  \\\n",
+       "0   I  0.9125    0.6875  0.3375   6.803880        3.061746        1.261553   \n",
+       "1   F  1.3000    1.0000  0.3250  17.704263        6.095142        5.854172   \n",
+       "2   F  1.3000    1.0000  0.3250  17.704263        6.095142        5.854172   \n",
+       "3   M  0.8250    0.5375  0.1875   3.246018        1.275727        0.751262   \n",
+       "4   F  1.3000    1.0000  0.3250  17.704263        6.095142        5.854172   \n",
+       "\n",
+       "   Shell Weight  Age  \n",
+       "0      2.083688    7  \n",
+       "1      4.819415   15  \n",
+       "2      4.819415   15  \n",
+       "3      0.992232    6  \n",
+       "4      4.819415   15  "
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_clear = pd.read_csv(\"D:/DataSets/CrabAge/data_clear.csv\")\n",
+    "df_clear.drop(columns = \"Unnamed: 0\", inplace = True)\n",
+    "df_clear.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# **Preparacion de Datos**"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# One Hot Encoding\n",
+    "\n",
+    "> Nuestra variable categorica `Sex` vamos a darle valores numéricos, para esto vamos a utilizar `one hot encoding`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from sklearn.preprocessing import OneHotEncoder"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "encoder = OneHotEncoder(sparse_output = False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[0., 1., 0.],\n",
+       "       [1., 0., 0.],\n",
+       "       [1., 0., 0.],\n",
+       "       ...,\n",
+       "       [1., 0., 0.],\n",
+       "       [1., 0., 0.],\n",
+       "       [0., 1., 0.]], shape=(3636, 3))"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "encoded_data = encoder.fit_transform(df_clear[[\"Sex\"]])\n",
+    "encoded_data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "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>Sex_F</th>\n",
+       "      <th>Sex_I</th>\n",
+       "      <th>Sex_M</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3631</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3632</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3633</th>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3634</th>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3635</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>3636 rows × 3 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      Sex_F  Sex_I  Sex_M\n",
+       "0       0.0    1.0    0.0\n",
+       "1       1.0    0.0    0.0\n",
+       "2       1.0    0.0    0.0\n",
+       "3       0.0    0.0    1.0\n",
+       "4       1.0    0.0    0.0\n",
+       "...     ...    ...    ...\n",
+       "3631    0.0    1.0    0.0\n",
+       "3632    0.0    0.0    1.0\n",
+       "3633    1.0    0.0    0.0\n",
+       "3634    1.0    0.0    0.0\n",
+       "3635    0.0    1.0    0.0\n",
+       "\n",
+       "[3636 rows x 3 columns]"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "encoded_df = pd.DataFrame(encoded_data, columns=encoder.get_feature_names_out([\"Sex\"]))\n",
+    "encoded_df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "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>Sex</th>\n",
+       "      <th>Length</th>\n",
+       "      <th>Diameter</th>\n",
+       "      <th>Height</th>\n",
+       "      <th>Weight</th>\n",
+       "      <th>Shucked Weight</th>\n",
+       "      <th>Viscera Weight</th>\n",
+       "      <th>Shell Weight</th>\n",
+       "      <th>Age</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>I</td>\n",
+       "      <td>0.9125</td>\n",
+       "      <td>0.6875</td>\n",
+       "      <td>0.3375</td>\n",
+       "      <td>6.803880</td>\n",
+       "      <td>3.061746</td>\n",
+       "      <td>1.261553</td>\n",
+       "      <td>2.083688</td>\n",
+       "      <td>7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>F</td>\n",
+       "      <td>1.3000</td>\n",
+       "      <td>1.0000</td>\n",
+       "      <td>0.3250</td>\n",
+       "      <td>17.704263</td>\n",
+       "      <td>6.095142</td>\n",
+       "      <td>5.854172</td>\n",
+       "      <td>4.819415</td>\n",
+       "      <td>15</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>F</td>\n",
+       "      <td>1.3000</td>\n",
+       "      <td>1.0000</td>\n",
+       "      <td>0.3250</td>\n",
+       "      <td>17.704263</td>\n",
+       "      <td>6.095142</td>\n",
+       "      <td>5.854172</td>\n",
+       "      <td>4.819415</td>\n",
+       "      <td>15</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>M</td>\n",
+       "      <td>0.8250</td>\n",
+       "      <td>0.5375</td>\n",
+       "      <td>0.1875</td>\n",
+       "      <td>3.246018</td>\n",
+       "      <td>1.275727</td>\n",
+       "      <td>0.751262</td>\n",
+       "      <td>0.992232</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>F</td>\n",
+       "      <td>1.3000</td>\n",
+       "      <td>1.0000</td>\n",
+       "      <td>0.3250</td>\n",
+       "      <td>17.704263</td>\n",
+       "      <td>6.095142</td>\n",
+       "      <td>5.854172</td>\n",
+       "      <td>4.819415</td>\n",
+       "      <td>15</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  Sex  Length  Diameter  Height     Weight  Shucked Weight  Viscera Weight  \\\n",
+       "0   I  0.9125    0.6875  0.3375   6.803880        3.061746        1.261553   \n",
+       "1   F  1.3000    1.0000  0.3250  17.704263        6.095142        5.854172   \n",
+       "2   F  1.3000    1.0000  0.3250  17.704263        6.095142        5.854172   \n",
+       "3   M  0.8250    0.5375  0.1875   3.246018        1.275727        0.751262   \n",
+       "4   F  1.3000    1.0000  0.3250  17.704263        6.095142        5.854172   \n",
+       "\n",
+       "   Shell Weight  Age  \n",
+       "0      2.083688    7  \n",
+       "1      4.819415   15  \n",
+       "2      4.819415   15  \n",
+       "3      0.992232    6  \n",
+       "4      4.819415   15  "
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_clear.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "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>Sex_F</th>\n",
+       "      <th>Sex_I</th>\n",
+       "      <th>Sex_M</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Sex_F  Sex_I  Sex_M\n",
+       "0    0.0    1.0    0.0\n",
+       "1    1.0    0.0    0.0\n",
+       "2    1.0    0.0    0.0\n",
+       "3    0.0    0.0    1.0\n",
+       "4    1.0    0.0    0.0"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "encoded_df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "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>Length</th>\n",
+       "      <th>Diameter</th>\n",
+       "      <th>Height</th>\n",
+       "      <th>Weight</th>\n",
+       "      <th>Shucked Weight</th>\n",
+       "      <th>Viscera Weight</th>\n",
+       "      <th>Shell Weight</th>\n",
+       "      <th>Age</th>\n",
+       "      <th>Sex_F</th>\n",
+       "      <th>Sex_I</th>\n",
+       "      <th>Sex_M</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0.9125</td>\n",
+       "      <td>0.6875</td>\n",
+       "      <td>0.3375</td>\n",
+       "      <td>6.803880</td>\n",
+       "      <td>3.061746</td>\n",
+       "      <td>1.261553</td>\n",
+       "      <td>2.083688</td>\n",
+       "      <td>7</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1.3000</td>\n",
+       "      <td>1.0000</td>\n",
+       "      <td>0.3250</td>\n",
+       "      <td>17.704263</td>\n",
+       "      <td>6.095142</td>\n",
+       "      <td>5.854172</td>\n",
+       "      <td>4.819415</td>\n",
+       "      <td>15</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1.3000</td>\n",
+       "      <td>1.0000</td>\n",
+       "      <td>0.3250</td>\n",
+       "      <td>17.704263</td>\n",
+       "      <td>6.095142</td>\n",
+       "      <td>5.854172</td>\n",
+       "      <td>4.819415</td>\n",
+       "      <td>15</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>0.8250</td>\n",
+       "      <td>0.5375</td>\n",
+       "      <td>0.1875</td>\n",
+       "      <td>3.246018</td>\n",
+       "      <td>1.275727</td>\n",
+       "      <td>0.751262</td>\n",
+       "      <td>0.992232</td>\n",
+       "      <td>6</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1.3000</td>\n",
+       "      <td>1.0000</td>\n",
+       "      <td>0.3250</td>\n",
+       "      <td>17.704263</td>\n",
+       "      <td>6.095142</td>\n",
+       "      <td>5.854172</td>\n",
+       "      <td>4.819415</td>\n",
+       "      <td>15</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</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",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3631</th>\n",
+       "      <td>1.5875</td>\n",
+       "      <td>1.2500</td>\n",
+       "      <td>0.4125</td>\n",
+       "      <td>42.212406</td>\n",
+       "      <td>20.269893</td>\n",
+       "      <td>9.766403</td>\n",
+       "      <td>10.248344</td>\n",
+       "      <td>13</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3632</th>\n",
+       "      <td>0.8250</td>\n",
+       "      <td>0.5375</td>\n",
+       "      <td>0.1875</td>\n",
+       "      <td>3.246018</td>\n",
+       "      <td>1.275727</td>\n",
+       "      <td>0.751262</td>\n",
+       "      <td>0.992232</td>\n",
+       "      <td>6</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3633</th>\n",
+       "      <td>1.5500</td>\n",
+       "      <td>1.1625</td>\n",
+       "      <td>0.3500</td>\n",
+       "      <td>28.661344</td>\n",
+       "      <td>13.579410</td>\n",
+       "      <td>6.761356</td>\n",
+       "      <td>7.229122</td>\n",
+       "      <td>8</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3634</th>\n",
+       "      <td>1.3000</td>\n",
+       "      <td>1.0000</td>\n",
+       "      <td>0.3250</td>\n",
+       "      <td>17.704263</td>\n",
+       "      <td>6.095142</td>\n",
+       "      <td>5.854172</td>\n",
+       "      <td>4.819415</td>\n",
+       "      <td>15</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3635</th>\n",
+       "      <td>1.5875</td>\n",
+       "      <td>1.2500</td>\n",
+       "      <td>0.4125</td>\n",
+       "      <td>42.212406</td>\n",
+       "      <td>20.269893</td>\n",
+       "      <td>9.766403</td>\n",
+       "      <td>10.248344</td>\n",
+       "      <td>13</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>3636 rows × 11 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      Length  Diameter  Height     Weight  Shucked Weight  Viscera Weight  \\\n",
+       "0     0.9125    0.6875  0.3375   6.803880        3.061746        1.261553   \n",
+       "1     1.3000    1.0000  0.3250  17.704263        6.095142        5.854172   \n",
+       "2     1.3000    1.0000  0.3250  17.704263        6.095142        5.854172   \n",
+       "3     0.8250    0.5375  0.1875   3.246018        1.275727        0.751262   \n",
+       "4     1.3000    1.0000  0.3250  17.704263        6.095142        5.854172   \n",
+       "...      ...       ...     ...        ...             ...             ...   \n",
+       "3631  1.5875    1.2500  0.4125  42.212406       20.269893        9.766403   \n",
+       "3632  0.8250    0.5375  0.1875   3.246018        1.275727        0.751262   \n",
+       "3633  1.5500    1.1625  0.3500  28.661344       13.579410        6.761356   \n",
+       "3634  1.3000    1.0000  0.3250  17.704263        6.095142        5.854172   \n",
+       "3635  1.5875    1.2500  0.4125  42.212406       20.269893        9.766403   \n",
+       "\n",
+       "      Shell Weight  Age  Sex_F  Sex_I  Sex_M  \n",
+       "0         2.083688    7    0.0    1.0    0.0  \n",
+       "1         4.819415   15    1.0    0.0    0.0  \n",
+       "2         4.819415   15    1.0    0.0    0.0  \n",
+       "3         0.992232    6    0.0    0.0    1.0  \n",
+       "4         4.819415   15    1.0    0.0    0.0  \n",
+       "...            ...  ...    ...    ...    ...  \n",
+       "3631     10.248344   13    0.0    1.0    0.0  \n",
+       "3632      0.992232    6    0.0    0.0    1.0  \n",
+       "3633      7.229122    8    1.0    0.0    0.0  \n",
+       "3634      4.819415   15    1.0    0.0    0.0  \n",
+       "3635     10.248344   13    0.0    1.0    0.0  \n",
+       "\n",
+       "[3636 rows x 11 columns]"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_clear = pd.concat([df_clear, encoded_df], axis=1)\n",
+    "\n",
+    "df_clear.drop(\"Sex\", axis = 1, inplace=True)\n",
+    "df_clear"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# **Modelado**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from sklearn.model_selection import train_test_split\n",
+    "from sklearn.linear_model import LinearRegression\n",
+    "from sklearn.ensemble import RandomForestRegressor\n",
+    "from sklearn.metrics import mean_squared_error"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "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>Length</th>\n",
+       "      <th>Diameter</th>\n",
+       "      <th>Height</th>\n",
+       "      <th>Weight</th>\n",
+       "      <th>Shucked Weight</th>\n",
+       "      <th>Viscera Weight</th>\n",
+       "      <th>Shell Weight</th>\n",
+       "      <th>Sex_F</th>\n",
+       "      <th>Sex_I</th>\n",
+       "      <th>Sex_M</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1075</th>\n",
+       "      <td>0.9125</td>\n",
+       "      <td>0.6875</td>\n",
+       "      <td>0.3375</td>\n",
+       "      <td>6.803880</td>\n",
+       "      <td>3.061746</td>\n",
+       "      <td>1.261553</td>\n",
+       "      <td>2.083688</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>734</th>\n",
+       "      <td>0.8250</td>\n",
+       "      <td>0.5375</td>\n",
+       "      <td>0.1875</td>\n",
+       "      <td>3.246018</td>\n",
+       "      <td>1.275727</td>\n",
+       "      <td>0.751262</td>\n",
+       "      <td>0.992232</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>513</th>\n",
+       "      <td>0.8250</td>\n",
+       "      <td>0.5375</td>\n",
+       "      <td>0.1875</td>\n",
+       "      <td>3.246018</td>\n",
+       "      <td>1.275727</td>\n",
+       "      <td>0.751262</td>\n",
+       "      <td>0.992232</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3010</th>\n",
+       "      <td>0.9125</td>\n",
+       "      <td>0.6875</td>\n",
+       "      <td>0.3375</td>\n",
+       "      <td>6.803880</td>\n",
+       "      <td>3.061746</td>\n",
+       "      <td>1.261553</td>\n",
+       "      <td>2.083688</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3588</th>\n",
+       "      <td>1.3625</td>\n",
+       "      <td>1.0500</td>\n",
+       "      <td>0.4375</td>\n",
+       "      <td>21.375523</td>\n",
+       "      <td>7.257472</td>\n",
+       "      <td>5.032036</td>\n",
+       "      <td>7.796112</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</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",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>406</th>\n",
+       "      <td>1.3000</td>\n",
+       "      <td>1.0000</td>\n",
+       "      <td>0.3250</td>\n",
+       "      <td>17.704263</td>\n",
+       "      <td>6.095142</td>\n",
+       "      <td>5.854172</td>\n",
+       "      <td>4.819415</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1414</th>\n",
+       "      <td>1.5875</td>\n",
+       "      <td>1.2500</td>\n",
+       "      <td>0.4125</td>\n",
+       "      <td>42.212406</td>\n",
+       "      <td>20.269893</td>\n",
+       "      <td>9.766403</td>\n",
+       "      <td>10.248344</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2191</th>\n",
+       "      <td>1.3250</td>\n",
+       "      <td>1.0125</td>\n",
+       "      <td>0.3750</td>\n",
+       "      <td>23.572609</td>\n",
+       "      <td>9.979024</td>\n",
+       "      <td>5.301356</td>\n",
+       "      <td>7.158249</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3313</th>\n",
+       "      <td>0.8625</td>\n",
+       "      <td>0.6375</td>\n",
+       "      <td>0.2250</td>\n",
+       "      <td>5.684075</td>\n",
+       "      <td>2.664853</td>\n",
+       "      <td>0.836310</td>\n",
+       "      <td>1.786018</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2671</th>\n",
+       "      <td>0.9125</td>\n",
+       "      <td>0.6875</td>\n",
+       "      <td>0.3375</td>\n",
+       "      <td>6.803880</td>\n",
+       "      <td>3.061746</td>\n",
+       "      <td>1.261553</td>\n",
+       "      <td>2.083688</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>2908 rows × 10 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      Length  Diameter  Height     Weight  Shucked Weight  Viscera Weight  \\\n",
+       "1075  0.9125    0.6875  0.3375   6.803880        3.061746        1.261553   \n",
+       "734   0.8250    0.5375  0.1875   3.246018        1.275727        0.751262   \n",
+       "513   0.8250    0.5375  0.1875   3.246018        1.275727        0.751262   \n",
+       "3010  0.9125    0.6875  0.3375   6.803880        3.061746        1.261553   \n",
+       "3588  1.3625    1.0500  0.4375  21.375523        7.257472        5.032036   \n",
+       "...      ...       ...     ...        ...             ...             ...   \n",
+       "406   1.3000    1.0000  0.3250  17.704263        6.095142        5.854172   \n",
+       "1414  1.5875    1.2500  0.4125  42.212406       20.269893        9.766403   \n",
+       "2191  1.3250    1.0125  0.3750  23.572609        9.979024        5.301356   \n",
+       "3313  0.8625    0.6375  0.2250   5.684075        2.664853        0.836310   \n",
+       "2671  0.9125    0.6875  0.3375   6.803880        3.061746        1.261553   \n",
+       "\n",
+       "      Shell Weight  Sex_F  Sex_I  Sex_M  \n",
+       "1075      2.083688    0.0    1.0    0.0  \n",
+       "734       0.992232    0.0    0.0    1.0  \n",
+       "513       0.992232    0.0    0.0    1.0  \n",
+       "3010      2.083688    0.0    1.0    0.0  \n",
+       "3588      7.796112    1.0    0.0    0.0  \n",
+       "...            ...    ...    ...    ...  \n",
+       "406       4.819415    1.0    0.0    0.0  \n",
+       "1414     10.248344    0.0    1.0    0.0  \n",
+       "2191      7.158249    0.0    0.0    1.0  \n",
+       "3313      1.786018    0.0    0.0    1.0  \n",
+       "2671      2.083688    0.0    1.0    0.0  \n",
+       "\n",
+       "[2908 rows x 10 columns]"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "X = df_clear.drop(\"Age\", axis = 1)\n",
+    "y = df_clear[\"Age\"]\n",
+    "\n",
+    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state = 17)\n",
+    "X_train"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "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",
+       "  max-height: 0;\n",
+       "  max-width: 0;\n",
+       "  overflow: hidden;\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",
+       "  max-height: 200px;\n",
+       "  max-width: 100%;\n",
+       "  overflow: auto;\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",
+       "</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>LinearRegression()</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-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow\"><div><div>LinearRegression</div></div><div><a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.6/modules/generated/sklearn.linear_model.LinearRegression.html\">?<span>Documentation for LinearRegression</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></div></label><div class=\"sk-toggleable__content fitted\"><pre>LinearRegression()</pre></div> </div></div></div></div>"
+      ],
+      "text/plain": [
+       "LinearRegression()"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rf_model = RandomForestRegressor(n_estimators = 100, random_state = 17)\n",
+    "rf_model.fit(X_train, y_train)\n",
+    "\n",
+    "lr_model = LinearRegression()\n",
+    "lr_model.fit(X_train, y_train)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "rf_predictions = rf_model.predict(X_test).round()\n",
+    "lr_predictions = lr_model.predict(X_test).round()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Random Forest MSE: 0.0\n",
+      "Linear Regression MSE: 0.3241758241758242\n"
+     ]
+    }
+   ],
+   "source": [
+    "rf_mse = mean_squared_error(y_test, rf_predictions)\n",
+    "lr_mse = mean_squared_error(y_test, lr_predictions)\n",
+    "\n",
+    "print(\"Random Forest MSE:\", rf_mse)\n",
+    "print(\"Linear Regression MSE:\", lr_mse)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Sample Predictions:\n",
+      "   - Random Forest => Predicted : 10.0, Actual: 10\n",
+      "   - linear Regression => Predicted : 11.0, Actual: 10\n",
+      "\n",
+      "   - Random Forest => Predicted : 10.0, Actual: 10\n",
+      "   - linear Regression => Predicted : 10.0, Actual: 10\n",
+      "\n",
+      "   - Random Forest => Predicted : 10.0, Actual: 10\n",
+      "   - linear Regression => Predicted : 11.0, Actual: 10\n",
+      "\n",
+      "   - Random Forest => Predicted : 6.0, Actual: 6\n",
+      "   - linear Regression => Predicted : 6.0, Actual: 6\n",
+      "\n",
+      "   - Random Forest => Predicted : 6.0, Actual: 6\n",
+      "   - linear Regression => Predicted : 6.0, Actual: 6\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"\\nSample Predictions:\")\n",
+    "num_samples = 5\n",
+    "\n",
+    "for i in range(num_samples):\n",
+    "    print(f\"   - Random Forest => Predicted : {rf_predictions[i]}, Actual: {y_test.iloc[i]}\")\n",
+    "    print(f\"   - linear Regression => Predicted : {lr_predictions[i]}, Actual: {y_test.iloc[i]}\")\n",
+    "    print()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# **Validación**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# **Despliegue**"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Sanchez",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.1"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}