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50 changes: 38 additions & 12 deletions lab-logistic-regression-with-python.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -123,9 +123,21 @@
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"execution_count": 16,
"metadata": {},
"outputs": [
{
"ename": "ModuleNotFoundError",
"evalue": "No module named 'piplite'",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)",
"Cell \u001b[1;32mIn[16], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mpiplite\u001b[39;00m\n\u001b[0;32m 2\u001b[0m \u001b[38;5;28;01mawait\u001b[39;00m piplite\u001b[38;5;241m.\u001b[39minstall([\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mpandas\u001b[39m\u001b[38;5;124m'\u001b[39m])\n\u001b[0;32m 3\u001b[0m \u001b[38;5;28;01mawait\u001b[39;00m piplite\u001b[38;5;241m.\u001b[39minstall([\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mmatplotlib\u001b[39m\u001b[38;5;124m'\u001b[39m])\n",
"\u001b[1;31mModuleNotFoundError\u001b[0m: No module named 'piplite'"
]
}
],
"source": [
"import piplite\n",
"await piplite.install(['pandas'])\n",
Expand All @@ -150,7 +162,7 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 20,
"metadata": {
"button": false,
"new_sheet": false,
Expand Down Expand Up @@ -226,7 +238,7 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 12,
"metadata": {
"button": false,
"new_sheet": false,
Expand Down Expand Up @@ -661,12 +673,26 @@
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"execution_count": 22,
"metadata": {},
"outputs": [
{
"ename": "NameError",
"evalue": "name 'LogisticRegression' is not defined",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mNameError\u001b[0m Traceback (most recent call last)",
"Cell \u001b[1;32mIn[22], line 2\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[38;5;66;03m# write your code here\u001b[39;00m\n\u001b[1;32m----> 2\u001b[0m LR2 \u001b[38;5;241m=\u001b[39m LogisticRegression(C\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m0.01\u001b[39m, solver\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124msag\u001b[39m\u001b[38;5;124m'\u001b[39m)\u001b[38;5;241m.\u001b[39mfit(X_train,y_train)\n\u001b[0;32m 3\u001b[0m yha2 \u001b[38;5;241m=\u001b[39m LR2\u001b[38;5;241m.\u001b[39mpredict_proba(X_test)\n\u001b[0;32m 4\u001b[0m \u001b[38;5;28mprint\u001b[39m (\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mLogLoss: : \u001b[39m\u001b[38;5;132;01m%.2f\u001b[39;00m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;241m%\u001b[39m log_loss(y_test, yha2))\n",
"\u001b[1;31mNameError\u001b[0m: name 'LogisticRegression' is not defined"
]
}
],
"source": [
"# write your code here\n",
"\n"
"LR2 = LogisticRegression(C=0.01, solver='sag').fit(X_train,y_train)\n",
"yha2 = LR2.predict_proba(X_test)\n",
"print (\"LogLoss: : %.2f\" % log_loss(y_test, yha2))"
]
},
{
Expand Down Expand Up @@ -695,9 +721,9 @@
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"display_name": "Python [conda env:base] *",
"language": "python",
"name": "python3"
"name": "conda-base-py"
},
"language_info": {
"codemirror_mode": {
Expand All @@ -709,7 +735,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.8"
"version": "3.12.3"
},
"widgets": {
"state": {},
Expand Down