Skip to content

Add files via upload #90

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
wants to merge 1 commit into
base: main
Choose a base branch
from
Open

Add files via upload #90

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
40 changes: 34 additions & 6 deletions lab-logistic-regression-with-python.ipynb
View file
Open in desktop
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": 1,
"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[1], 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 Down Expand Up @@ -339,7 +351,14 @@
},
"outputs": [],
"source": [
"# write your code here\n"
"\n",
"rows, cols = churn_df.shape\n",
"print(f\"Number of rows: {rows}\")\n",
"print(f\"Number of columns: {cols}\")\n",
"\n",
"\n",
"print(\"Column names:\")\n",
"print(churn_df.columns.tolist())"
]
},
{
Expand Down Expand Up @@ -665,7 +684,16 @@
"metadata": {},
"outputs": [],
"source": [
"# write your code here\n",
"from sklearn.linear_model import LogisticRegression\n",
"from sklearn.metrics import log_loss\n",
"\n",
"LR_new = LogisticRegression(C=0.1, solver='saga').fit(X_train, y_train)\n",
"\n",
"yhat_prob_new = LR_new.predict_proba(X_test)\n",
"\n",
"log_loss_value = log_loss(y_test, yhat_prob_new)\n",
"\n",
"print(f\"New Log Loss value: {log_loss_value:.4f}\")\n",
"\n"
]
},
Expand Down Expand Up @@ -709,7 +737,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.8"
"version": "3.11.11"
},
"widgets": {
"state": {},
Expand Down