Merge pull request #13 from eahussein/hack

clear output

Author: eahussein

notebooks/.ipynb_checkpoints/tutorial1-checkpoint.ipynb

@@ -46,7 +46,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "id": "afe38816-b8e6-4261-a331-cd9af0a89f80",
    "metadata": {},
    "outputs": [],
@@ -74,18 +74,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "id": "2f0f6cd0-c654-4fb5-9824-e6d153394237",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "(503, 2074)\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "# ___Cell no. 2___\n",
     "\n",
@@ -105,32 +97,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "id": "2a393b7e-4095-452b-bc26-a6bcf3001399",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0      0\n",
-       "1      0\n",
-       "2      1\n",
-       "3      1\n",
-       "4      0\n",
-       "      ..\n",
-       "498    1\n",
-       "499    1\n",
-       "500    0\n",
-       "501    1\n",
-       "502    1\n",
-       "Name: Condition, Length: 503, dtype: int64"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "# ___Cell no. 3___\n",
     "\n",
@@ -156,7 +126,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "id": "b3a1dcb5-4530-4075-ad85-15a14aa9871b",
    "metadata": {},
    "outputs": [],
@@ -168,19 +138,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "id": "ac6a0f61-8f8b-4d4a-9d8b-e7312dd2dd46",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "(352, 2074)\n",
-      "(352,)\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "# ___Cell no. 5___\n",
     "\n",
@@ -206,7 +167,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": null,
    "id": "592805f0-40eb-45dc-ac8b-78cb21e7049e",
    "metadata": {},
    "outputs": [],
@@ -218,21 +179,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": null,
    "id": "3189f8e7-1286-4f36-a5d5-da0d478131c8",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "LogisticRegression(random_state=0, solver='newton-cg')"
-      ]
-     },
-     "execution_count": 8,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "# ___Cell no. 7___\n",
     "\n",
@@ -250,7 +200,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": null,
    "id": "9ca6a19c-bad0-4b96-8919-74d14ad8b914",
    "metadata": {},
    "outputs": [],
@@ -262,26 +212,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": null,
    "id": "49e4f905-ae06-4ddc-ad9f-2f71ae12483b",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Accuracy score is 0.7947019867549668\n"
-     ]
-    },
-    {
-     "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"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "# ___Cell no. 9___\n",
     "y_pred = LR.predict(Xtest)\n",
@@ -298,18 +232,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": null,
    "id": "ec14014c-e88d-49c5-8b56-448e80466684",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Precision score is 0.7647058823529411\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "# ___Cell no. 10___\n",
     "print(\"Precision score is\", precision_score(Ytest.values, y_pred))"