{ "cells": [ { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Selected feature: Area_worst\n" ] }, { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import numpy as np\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "from sklearn.feature_selection import SelectKBest, chi2\n", "from sklearn.preprocessing import StandardScaler\n", "from sklearn.linear_model import LogisticRegression\n", "from sklearn.utils import resample # For bootstrapping\n", "\n", "# Load dataset\n", "url = \"https://archive.ics.uci.edu/ml/machine-learning-databases/breast-cancer-wisconsin/wdbc.data\"\n", "columns = [\"ID\", \"Diagnosis\", \"Radius_mean\", \"Texture_mean\", \"Perimeter_mean\", \"Area_mean\",\n", " \"Smoothness_mean\", \"Compactness_mean\", \"Concavity_mean\", \"Concave_points_mean\",\n", " \"Symmetry_mean\", \"Fractal_dimension_mean\", \"Radius_se\", \"Texture_se\", \n", " \"Perimeter_se\", \"Area_se\", \"Smoothness_se\", \"Compactness_se\", \"Concavity_se\", \n", " \"Concave_points_se\", \"Symmetry_se\", \"Fractal_dimension_se\", \"Radius_worst\",\n", " \"Texture_worst\", \"Perimeter_worst\", \"Area_worst\", \"Smoothness_worst\", \n", " \"Compactness_worst\", \"Concavity_worst\", \"Concave_points_worst\", \n", " \"Symmetry_worst\", \"Fractal_dimension_worst\"]\n", "\n", "df = pd.read_csv(url, names=columns)\n", "\n", "# Drop the 'ID' column and convert diagnosis to numeric (Malignant = 1, Benign = 0)\n", "df.drop(columns=[\"ID\"], inplace=True)\n", "df[\"Diagnosis\"] = df[\"Diagnosis\"].map({\"M\": 1, \"B\": 0})\n", "\n", "# Select the best single feature using the chi-square test\n", "selector = SelectKBest(chi2, k=1)\n", "X_new = selector.fit_transform(df.drop(columns=[\"Diagnosis\"]), df[\"Diagnosis\"])\n", "selected_feature = df.drop(columns=[\"Diagnosis\"]).columns[selector.get_support()][0]\n", "print(f\"Selected feature: {selected_feature}\")\n", "\n", "# Extract the selected feature\n", "X = df[[selected_feature]].values\n", "y = df[\"Diagnosis\"].values\n", "\n", "# Standardize the feature\n", "scaler = StandardScaler()\n", "X_scaled = scaler.fit_transform(X)\n", "\n", "# Fit the Logistic Regression model\n", "logreg = LogisticRegression(solver=\"liblinear\")\n", "logreg.fit(X_scaled, y)\n", "\n", "# Generate values for prediction\n", "X_range = np.linspace(X_scaled.min(), X_scaled.max(), 100).reshape(-1, 1)\n", "y_pred = logreg.predict_proba(X_range)[:, 1] # Predicted probability of malignancy\n", "\n", "# --- BOOTSTRAPPING ---\n", "n_bootstraps = 1000 # Number of bootstrap samples\n", "bootstrap_preds = np.zeros((n_bootstraps, len(X_range))) # Store predictions\n", "\n", "# Perform bootstrapping\n", "for i in range(n_bootstraps):\n", " X_resampled, y_resampled = resample(X_scaled, y, replace=True) # Resample data\n", " logreg_boot = LogisticRegression(solver=\"liblinear\") # New model\n", " logreg_boot.fit(X_resampled, y_resampled) # Train on bootstrap sample\n", " bootstrap_preds[i] = logreg_boot.predict_proba(X_range)[:, 1] # Store predictions\n", "\n", "# Compute confidence intervals (5th and 95th percentile for 95% CI)\n", "lower_bound = np.percentile(bootstrap_preds, 2.5, axis=0)\n", "upper_bound = np.percentile(bootstrap_preds, 97.5, axis=0)\n", "\n", "# --- PLOTTING RESULTS ---\n", "plt.figure(figsize=(8, 6))\n", "\n", "# Plot logistic regression curve\n", "plt.plot(X_range, y_pred, color=\"blue\", label=\"Logistic Regression Curve\")\n", "\n", "# Plot confidence interval as shaded region\n", "plt.fill_between(X_range.flatten(), lower_bound, upper_bound, color=\"blue\", alpha=0.2, label=\"95% CI (Bootstrap)\")\n", "\n", "# Scatter plot of actual data points\n", "plt.scatter(X_scaled, y, color=\"red\", alpha=0.5, label=\"Data Points\")\n", "\n", "# Labels and title\n", "plt.xlabel(f\"{selected_feature} (Standardized)\")\n", "plt.ylabel(\"Probability of Malignant (1)\")\n", "plt.title(f\"Logistic Regression with 95% Bootstrap CI for {selected_feature}\")\n", "plt.legend()\n", "plt.grid(True)\n", "\n", "plt.show()\n" ] } ], "metadata": { "kernelspec": { "display_name": "base", "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": "3.12.7" } }, "nbformat": 4, "nbformat_minor": 2 }