Merge pull request #12 from eahussein/hack

Done

Author: eahussein

notebooks/.ipynb_checkpoints/tutorial1-checkpoint.ipynb

@@ -8,6 +8,22 @@
     "# Tutorial 2: Baseline Calculation."
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "6990d828-0bd2-4980-bccf-4ac1c45e695c",
+   "metadata": {},
+   "source": [
+    "---"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "00b716c0-15ec-4865-9fc3-ef48c93f6229",
+   "metadata": {},
+   "source": [
+    "### Introduction"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "d2cf0528-c3f2-4596-91b8-2bc5c44e5b89",
@@ -30,7 +46,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 2,
    "id": "afe38816-b8e6-4261-a331-cd9af0a89f80",
    "metadata": {},
    "outputs": [],
@@ -58,7 +74,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 3,
    "id": "2f0f6cd0-c654-4fb5-9824-e6d153394237",
    "metadata": {},
    "outputs": [
@@ -89,7 +105,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 4,
    "id": "2a393b7e-4095-452b-bc26-a6bcf3001399",
    "metadata": {},
    "outputs": [
@@ -110,7 +126,7 @@
        "Name: Condition, Length: 503, dtype: int64"
       ]
      },
-     "execution_count": 15,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -140,7 +156,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 5,
    "id": "b3a1dcb5-4530-4075-ad85-15a14aa9871b",
    "metadata": {},
    "outputs": [],
@@ -152,7 +168,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 6,
    "id": "ac6a0f61-8f8b-4d4a-9d8b-e7312dd2dd46",
    "metadata": {},
    "outputs": [
@@ -190,7 +206,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 7,
    "id": "592805f0-40eb-45dc-ac8b-78cb21e7049e",
    "metadata": {},
    "outputs": [],
@@ -202,7 +218,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 8,
    "id": "3189f8e7-1286-4f36-a5d5-da0d478131c8",
    "metadata": {},
    "outputs": [
@@ -212,7 +228,7 @@
        "LogisticRegression(random_state=0, solver='newton-cg')"
       ]
      },
-     "execution_count": 19,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -234,7 +250,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 9,
    "id": "9ca6a19c-bad0-4b96-8919-74d14ad8b914",
    "metadata": {},
    "outputs": [],
@@ -246,32 +262,28 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 11,
    "id": "49e4f905-ae06-4ddc-ad9f-2f71ae12483b",
    "metadata": {},
    "outputs": [
     {
-     "name": "stderr",
+     "name": "stdout",
      "output_type": "stream",
      "text": [
-      "/users/hussein/source/apple_classification/appleVer/lib/python3.8/site-packages/sklearn/utils/validation.py:1688: FutureWarning: Feature names only support names that are all strings. Got feature names with dtypes: ['float']. An error will be raised in 1.2.\n",
-      "  warnings.warn(\n"
+      "Accuracy score is 0.7947019867549668\n"
      ]
     },
     {
-     "data": {
-      "text/plain": [
-       "0.7947019867549668"
-      ]
-     },
-     "execution_count": 21,
-     "metadata": {},
-     "output_type": "execute_result"
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/users/hussein/.local/lib/python3.8/site-packages/sklearn/utils/validation.py:1688: FutureWarning: Feature names only support names that are all strings. Got feature names with dtypes: ['float']. An error will be raised in 1.2.\n",
+      "  warnings.warn(\n"
+     ]
     }
    ],
    "source": [
     "# ___Cell no. 9___\n",
-    "e\n",
     "y_pred = LR.predict(Xtest)\n",
     "print(\"Accuracy score is\", accuracy_score(Ytest.values, y_pred))"
    ]
@@ -286,24 +298,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 13,
    "id": "ec14014c-e88d-49c5-8b56-448e80466684",
    "metadata": {},
    "outputs": [
     {
-     "data": {
-      "text/plain": [
-       "0.7647058823529411"
-      ]
-     },
-     "execution_count": 22,
-     "metadata": {},
-     "output_type": "execute_result"
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Precision score is 0.7647058823529411\n"
+     ]
     }
    ],
    "source": [
     "# ___Cell no. 10___\n",
-    "print(\"Precision score is\", precision_score(Ytest.values, y_pred)"
+    "print(\"Precision score is\", precision_score(Ytest.values, y_pred))"
    ]
   },
   {
@@ -316,34 +325,34 @@
   },
   {
    "cell_type": "markdown",
-   "id": "2848557c-c043-4bea-b2f5-00e151ed887f",
+   "id": "7265d92b-0cf8-4ee2-b34b-49959209bc8c",
    "metadata": {},
    "source": [
-    "---"
+    "**Exercise 1:** Perform LR on the other two data sets."
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "7265d92b-0cf8-4ee2-b34b-49959209bc8c",
+   "id": "e52169be-ba02-41cd-a585-080a2deeaff8",
    "metadata": {},
    "source": [
-    "**Exercise 1:** Perform LR on the other two data sets."
+    "---"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "c4372bed-6a77-44a7-b3ab-b1c8eb53d12c",
+   "id": "076dd6f3-e86f-4e8d-95ca-04938d45a5bc",
    "metadata": {},
    "outputs": [],
    "source": []
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "NEE_ker",
+   "display_name": "Python 3",
    "language": "python",
-   "name": "nee_ker"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -355,7 +364,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.7"
+   "version": "3.8.3"
   },
   "varInspector": {
    "cols": {