diff --git a/ML_Project2_Volleyvission.ipynb b/ML_Project2_Volleyvission.ipynb new file mode 100644 index 0000000..b94d215 --- /dev/null +++ b/ML_Project2_Volleyvission.ipynb @@ -0,0 +1,808 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "SxLhf_mYEtEx", + "outputId": "631676bd-ab2f-4ff5-c288-7927926fe615" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Are there NaN values in X before preprocessing? False\n", + "Are there NaN values in y before preprocessing? False\n", + "Are there NaN values in X after preprocessing? False\n", + "k-Fold Cross-Validation MSE (with proper preprocessing): 3231.9376\n", + "Bootstrap .632 MSE: 1248.3749\n" + ] + } + ], + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "from sklearn.model_selection import KFold\n", + "from sklearn.utils import resample\n", + "from sklearn.metrics import mean_squared_error\n", + "import seaborn as sns\n", + "import matplotlib.pyplot as plt\n", + "from sklearn.preprocessing import RobustScaler\n", + "from math import pi\n", + "from sklearn.model_selection import learning_curve\n", + "from sklearn.linear_model import LinearRegression\n", + "from sklearn.preprocessing import PolynomialFeatures\n", + "from sklearn.pipeline import make_pipeline\n", + "from sklearn.linear_model import LinearRegression\n", + "from sklearn.metrics import r2_score, mean_absolute_error\n", + "from sklearn.metrics import roc_curve, auc\n", + "\n", + "# Load the dataset\n", + "file_path = 'tabula-mvb_stats_2024.csv'\n", + "data = pd.read_csv(file_path)\n", + "\n", + "target = \"PTS\"\n", + "features = [\"SP\", \"K\", \"K/S\", \"DIG\", \"DIG/S\", \"BS\", \"BA\", \"BLK\", \"BLK/S\"]\n", + "\n", + "data_cleaned = data[features + [target]].dropna()\n", + "\n", + "lower_bounds = data_cleaned[features].quantile(0.01)\n", + "upper_bounds = data_cleaned[features].quantile(0.99)\n", + "\n", + "data_cleaned[features] = data_cleaned[features].clip(lower=lower_bounds, upper=upper_bounds, axis=1)\n", + "\n", + "\n", + "X = data_cleaned[features].to_numpy()\n", + "y = data_cleaned[target].to_numpy()\n", + "\n", + "scaler = RobustScaler()\n", + "X_standardized = scaler.fit_transform(X)\n", + "\n", + "print(\"Are there NaN values in X before preprocessing?\", np.isnan(X).any())\n", + "print(\"Are there NaN values in y before preprocessing?\", np.isnan(y).any())\n", + "print(\"Are there NaN values in X after preprocessing?\", np.isnan(X_standardized).any())\n", + "\n", + "def linear_regression_predict(X, theta):\n", + " return np.dot(X, theta)\n", + "\n", + "def linear_regression_gradient_descent(X, Y, theta, alpha, iterations, clip_value=1e3):\n", + " \"\"\"\n", + " Performs gradient descent for linear regression with gradient clipping.\n", + " \"\"\"\n", + " m = len(Y)\n", + " for iter_num in range(iterations):\n", + " predictions = linear_regression_predict(X, theta)\n", + " errors = predictions - Y\n", + " gradients = (1 / m) * np.dot(X.T, errors)\n", + "\n", + " gradients = np.clip(gradients, -clip_value, clip_value)\n", + "\n", + " if np.isnan(gradients).any() or np.isinf(gradients).any():\n", + " print(f\"Iteration {iter_num}: Invalid gradients detected. Skipping update.\")\n", + " break\n", + "\n", + " theta -= alpha * gradients\n", + "\n", + " if np.isnan(theta).any() or np.isinf(theta).any():\n", + " print(\"Invalid theta values detected after gradient descent.\")\n", + "\n", + " return theta\n", + "\n", + "# k-Fold Cross-Validation with Preprocessing in Each Fold\n", + "def k_fold_cross_validation_with_selection(X, y, k=5):\n", + " kf = KFold(n_splits=k, shuffle=True, random_state=42)\n", + " mse_scores = []\n", + "\n", + " for train_idx, test_idx in kf.split(X):\n", + "\n", + " X_train, X_test = X[train_idx], X[test_idx]\n", + " y_train, y_test = y[train_idx], y[test_idx]\n", + "\n", + " scaler = RobustScaler()\n", + " X_train = scaler.fit_transform(X_train)\n", + " X_test = scaler.transform(X_test)\n", + "\n", + " theta = np.zeros(X_train.shape[1])\n", + " theta = linear_regression_gradient_descent(X_train, y_train, theta, alpha=0.01, iterations=1000)\n", + "\n", + " # Predict and calculate MSE\n", + " y_pred = linear_regression_predict(X_test, theta)\n", + " mse = np.mean((y_pred - y_test) ** 2)\n", + " mse_scores.append(mse)\n", + "\n", + " return np.mean(mse_scores)\n", + "\n", + "# Bootstrap with .632 Estimator\n", + "def bootstrap_632(X, y, n_iterations=100):\n", + " \"\"\"\n", + " Implements the .632 bootstrap estimator with robust error handling.\n", + " \"\"\"\n", + " n = len(y)\n", + " mse_in = []\n", + " mse_out = []\n", + "\n", + " for i in range(n_iterations):\n", + " indices = np.random.choice(range(n), size=n, replace=True)\n", + " X_resampled, y_resampled = X[indices], y[indices]\n", + "\n", + " mask = np.ones(n, dtype=bool)\n", + " mask[indices] = False\n", + " X_out, y_out = X[mask], y[mask]\n", + "\n", + " if X_out.shape[0] == 0 or y_out.shape[0] == 0:\n", + " print(f\"Iteration {i}: Empty out-of-bag sample. Skipping iteration.\")\n", + " continue\n", + "\n", + " theta = np.zeros(X_resampled.shape[1])\n", + " theta = linear_regression_gradient_descent(X_resampled, y_resampled, theta, alpha=0.01, iterations=1000)\n", + "\n", + " if np.isnan(theta).any() or np.isinf(theta).any():\n", + " print(f\"Iteration {i}: Invalid theta detected. Skipping iteration.\")\n", + " continue\n", + "\n", + " y_pred_in = linear_regression_predict(X_resampled, theta)\n", + " y_pred_out = linear_regression_predict(X_out, theta)\n", + "\n", + " if np.isnan(y_pred_out).any() or np.isinf(y_pred_out).any():\n", + " print(f\"Iteration {i}: Invalid predictions detected. Skipping iteration.\")\n", + " continue\n", + "\n", + " mse_in.append(mean_squared_error(y_resampled, y_pred_in))\n", + " mse_out.append(mean_squared_error(y_out, y_pred_out))\n", + "\n", + " # Compute .632 bootstrap estimator\n", + " if len(mse_out) == 0:\n", + " print(\"Error: No valid out-of-bag samples found.\")\n", + " return np.nan\n", + "\n", + " err_in = np.mean(mse_in)\n", + " err_out = np.mean(mse_out)\n", + " err_632 = 0.368 * err_in + 0.632 * err_out\n", + " return err_632\n", + "\n", + "# Perform k-Fold Cross-Validation\n", + "kfold_mse = k_fold_cross_validation_with_selection(X_standardized, y, k=5)\n", + "print(f\"k-Fold Cross-Validation MSE (with proper preprocessing): {kfold_mse:.4f}\")\n", + "\n", + "# Perform Bootstrap with .632 estimator\n", + "bootstrap_632_mse = bootstrap_632(X_standardized, y, n_iterations=100)\n", + "print(f\"Bootstrap .632 MSE: {bootstrap_632_mse:.4f}\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "EbbWCR0eQgne", + "outputId": "49d64ec5-7b7a-4b4d-c7c1-657858ce7aca" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "R² Score: 0.9995\n", + "Mean Absolute Error (MAE): 1.7995\n" + ] + } + ], + "source": [ + "# Model Accuracy\n", + "# R² Score\n", + "model = LinearRegression()\n", + "model.fit(X_standardized, y)\n", + "\n", + "# Predict using the trained model\n", + "y_pred = model.predict(X_standardized)\n", + "\n", + "r2 = r2_score(y, y_pred)\n", + "print(f\"R² Score: {r2:.4f}\")\n", + "\n", + "# Mean Absolute Error (MAE)\n", + "mae = mean_absolute_error(y, y_pred)\n", + "print(f\"Mean Absolute Error (MAE): {mae:.4f}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 564 + }, + "id": "gZlr6jXAWrGz", + "outputId": "3843e362-c0fb-4561-ef66-fb53d5c1f001" + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "#ROC Curve\n", + "threshold = y.mean()\n", + "y_binary = (y > threshold).astype(int)\n", + "y_pred_binary = (y_pred > threshold).astype(int)\n", + "\n", + "# Compute ROC curve\n", + "fpr, tpr, _ = roc_curve(y_binary, y_pred_binary)\n", + "roc_auc = auc(fpr, tpr)\n", + "\n", + "# Plot ROC curve\n", + "plt.figure(figsize=(8, 6))\n", + "plt.plot(fpr, tpr, color=\"darkorange\", lw=2, label=f\"ROC Curve (AUC = {roc_auc:.2f})\")\n", + "plt.plot([0, 1], [0, 1], color=\"navy\", linestyle=\"--\", lw=2)\n", + "plt.title(\"Receiver Operating Characteristic (ROC) Curve\")\n", + "plt.xlabel(\"False Positive Rate\")\n", + "plt.ylabel(\"True Positive Rate\")\n", + "plt.legend(loc=\"lower right\")\n", + "plt.grid()\n", + "plt.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 699 + }, + "id": "IdMNT8QdXh1H", + "outputId": "9fa3c987-0894-46c7-8208-baf1fd67497f" + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Correlation heatmap\n", + "plt.figure(figsize=(10, 8))\n", + "correlation_matrix = data_cleaned.corr()\n", + "sns.heatmap(correlation_matrix, annot=True, cmap=\"coolwarm\", fmt=\".2f\")\n", + "plt.title(\"Correlation Between Player Statistics and Points Scored (PTS)\")\n", + "plt.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 564 + }, + "id": "8qjQgDB_WwMV", + "outputId": "2848c4ae-fae6-4ac6-e4f9-3f5f7e33a3cd" + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "\n", + "# learning Cruve\n", + "train_sizes, train_scores, test_scores = learning_curve(\n", + " estimator=LinearRegression(),\n", + " X=X_standardized,\n", + " y=y,\n", + " train_sizes=np.linspace(0.1, 1.0, 10),\n", + " cv=5,\n", + " scoring='neg_mean_squared_error',\n", + " random_state=42,\n", + ")\n", + "\n", + "train_mean = -train_scores.mean(axis=1)\n", + "test_mean = -test_scores.mean(axis=1)\n", + "\n", + "plt.figure(figsize=(10, 6))\n", + "plt.plot(train_sizes, train_mean, label=\"Training Error\", marker='o')\n", + "plt.plot(train_sizes, test_mean, label=\"Validation Error\", marker='s')\n", + "plt.title(\"Learning Curve: Training vs. Validation Error\")\n", + "plt.xlabel(\"Training Set Size\")\n", + "plt.ylabel(\"Mean Squared Error\")\n", + "plt.legend()\n", + "plt.grid()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 564 + }, + "id": "yvY-FEpyW0-j", + "outputId": "9e69f173-af38-41ec-d6ee-bf051755b663" + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Bias-variance trade off\n", + "degrees = [1, 2, 3, 4, 5]\n", + "train_errors, test_errors = [], []\n", + "\n", + "for degree in degrees:\n", + " model = make_pipeline(PolynomialFeatures(degree), LinearRegression())\n", + " model.fit(X_standardized, y)\n", + "\n", + " train_errors.append(mean_squared_error(y, model.predict(X_standardized)))\n", + " test_errors.append(bootstrap_632(X_standardized, y))\n", + "\n", + "plt.figure(figsize=(8, 6))\n", + "plt.plot(degrees, train_errors, label=\"Training Error\", marker='o')\n", + "plt.plot(degrees, test_errors, label=\"Bootstrap .632 Error\", marker='s')\n", + "plt.title(\"Bias-Variance Trade-Off\")\n", + "plt.xlabel(\"Model Complexity (Polynomial Degree)\")\n", + "plt.ylabel(\"Mean Squared Error\")\n", + "plt.legend()\n", + "plt.grid()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 564 + }, + "id": "Jc5BAaQgW4Xv", + "outputId": "19c10baa-6fec-46ee-907c-eec551f76a58" + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Residual Plot\n", + "model = LinearRegression()\n", + "model.fit(X_standardized, y)\n", + "y_pred = model.predict(X_standardized)\n", + "\n", + "residuals = y - y_pred\n", + "\n", + "plt.figure(figsize=(8, 6))\n", + "sns.scatterplot(x=y_pred, y=residuals)\n", + "plt.axhline(0, linestyle='--', color='red', label=\"Zero Residual Line\")\n", + "plt.title(\"Residual Plot: Predicted Points vs. Residuals\")\n", + "plt.xlabel(\"Predicted Points (PTS)\")\n", + "plt.ylabel(\"Residuals\")\n", + "plt.legend()\n", + "plt.grid()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 651 + }, + "id": "IM0rJoHAW8B3", + "outputId": "4ffefb03-314c-42af-e243-5830348619e6" + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "\n", + "# Feature Importance Visualization\n", + "importances = np.abs(model.coef_)\n", + "feature_importance = pd.DataFrame({\"Feature\": features, \"Importance\": importances})\n", + "feature_importance = feature_importance.sort_values(by=\"Importance\", ascending=False)\n", + "\n", + "plt.figure(figsize=(10, 6))\n", + "sns.barplot(x=\"Importance\", y=\"Feature\", data=feature_importance, palette=\"viridis\")\n", + "plt.title(\"Feature Importance for Predicting Points Scored (PTS)\")\n", + "plt.xlabel(\"Coefficient Magnitude\")\n", + "plt.ylabel(\"Feature\")\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 743 + }, + "id": "45eHU4k8W_om", + "outputId": "dd552832-8a69-4f6f-a2c2-8978e8e3569a" + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Bar chart of total points scored by each player\n", + "player_names = data['Player'] if 'Player' in data.columns else range(len(data))\n", + "points_scored = data_cleaned['PTS']\n", + "\n", + "plt.figure(figsize=(12, 6))\n", + "sns.barplot(x=player_names, y=points_scored, palette=\"viridis\")\n", + "plt.title(\"Total Points Scored by Each Player\")\n", + "plt.xlabel(\"Player\")\n", + "plt.ylabel(\"Points Scored (PTS)\")\n", + "plt.xticks(rotation=45)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 636 + }, + "id": "EOtMETpiXCqV", + "outputId": "1fc2ae8e-3e76-421d-995e-7c7fb7826ca9" + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/var/folders/v0/r5w5ydbd3fq8jsrpddtvxkgr0000gn/T/ipykernel_62993/2284169935.py:3: UserWarning: Ignoring `palette` because no `hue` variable has been assigned.\n", + " sns.scatterplot(x=data_cleaned['K'], y=data_cleaned['PTS'], hue=data_cleaned['Player'] if 'Player' in data_cleaned else None, palette=\"coolwarm\", s=100)\n", + "No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Scatter Plot: Points Scored vs. Kills\n", + "plt.figure(figsize=(8, 6))\n", + "sns.scatterplot(x=data_cleaned['K'], y=data_cleaned['PTS'], hue=data_cleaned['Player'] if 'Player' in data_cleaned else None, palette=\"coolwarm\", s=100)\n", + "plt.title(\"Points Scored vs. Kills\")\n", + "plt.xlabel(\"Kills (K)\")\n", + "plt.ylabel(\"Points Scored (PTS)\")\n", + "plt.legend(title=\"Player\", bbox_to_anchor=(1.05, 1), loc='upper left')\n", + "plt.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 564 + }, + "id": "jtLIQPs2XFrh", + "outputId": "401a4389-72ba-4dcc-80c8-d842097acc3c" + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/anaconda3/lib/python3.11/site-packages/seaborn/_oldcore.py:1119: FutureWarning: use_inf_as_na option is deprecated and will be removed in a future version. Convert inf values to NaN before operating instead.\n", + " with pd.option_context('mode.use_inf_as_na', True):\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Distribution of the target variable (PTS)\n", + "plt.figure(figsize=(8, 6))\n", + "sns.histplot(data_cleaned[target], kde=True, bins=10, color='blue', alpha=0.6)\n", + "plt.title(\"Distribution of Points Scored (PTS)\")\n", + "plt.xlabel(\"Points Scored (PTS)\")\n", + "plt.ylabel(\"Number of Players\")\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 656 + }, + "id": "LH6cAHpVXIgz", + "outputId": "8039e53c-0b14-4125-a3af-a605cace9b66" + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Heatmap: Set Performance Efficiency (K/S, DIG/S, BLK/S)\n", + "set_metrics = ['K/S', 'DIG/S', 'BLK/S']\n", + "plt.figure(figsize=(8, 6))\n", + "sns.heatmap(data_cleaned[set_metrics].transpose(), annot=True, cmap=\"YlGnBu\", cbar_kws={'label': 'Performance Metric'})\n", + "plt.title(\"Set Performance Metrics for Players\")\n", + "plt.xlabel(\"Player\")\n", + "plt.ylabel(\"Metric\")\n", + "plt.xticks(ticks=range(len(data_cleaned)), labels=data['Player'] if 'Player' in data.columns else range(len(data_cleaned)), rotation=45)\n", + "plt.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 564 + }, + "id": "JaVHG7hKXMC4", + "outputId": "2c1642bf-287f-4425-e283-fe23631d432f" + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/anaconda3/lib/python3.11/site-packages/seaborn/_oldcore.py:1119: FutureWarning: use_inf_as_na option is deprecated and will be removed in a future version. Convert inf values to NaN before operating instead.\n", + " with pd.option_context('mode.use_inf_as_na', True):\n", + "/opt/anaconda3/lib/python3.11/site-packages/seaborn/_oldcore.py:1119: FutureWarning: use_inf_as_na option is deprecated and will be removed in a future version. Convert inf values to NaN before operating instead.\n", + " with pd.option_context('mode.use_inf_as_na', True):\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Distribution of Defensive Skills (DIG and BLK)\n", + "plt.figure(figsize=(10, 6))\n", + "sns.kdeplot(data_cleaned['DIG'], fill=True, label=\"Digs (DIG)\", color=\"teal\")\n", + "sns.kdeplot(data_cleaned['BLK'], fill=True, label=\"Blocks (BLK)\", color=\"coral\")\n", + "plt.title(\"Distribution of Defensive Skills (DIG and BLK)\")\n", + "plt.xlabel(\"Skill Count\")\n", + "plt.ylabel(\"Density\")\n", + "plt.legend()\n", + "plt.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 1000 + }, + "id": "1JxJkdcSXO7e", + "outputId": "cf407034-a7b2-41a1-c54f-2bd76acdb3c2" + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/anaconda3/lib/python3.11/site-packages/seaborn/_oldcore.py:1119: FutureWarning: use_inf_as_na option is deprecated and will be removed in a future version. Convert inf values to NaN before operating instead.\n", + " with pd.option_context('mode.use_inf_as_na', True):\n", + "/opt/anaconda3/lib/python3.11/site-packages/seaborn/_oldcore.py:1119: FutureWarning: use_inf_as_na option is deprecated and will be removed in a future version. Convert inf values to NaN before operating instead.\n", + " with pd.option_context('mode.use_inf_as_na', True):\n", + "/opt/anaconda3/lib/python3.11/site-packages/seaborn/_oldcore.py:1119: FutureWarning: use_inf_as_na option is deprecated and will be removed in a future version. Convert inf values to NaN before operating instead.\n", + " with pd.option_context('mode.use_inf_as_na', True):\n", + "/opt/anaconda3/lib/python3.11/site-packages/seaborn/_oldcore.py:1119: FutureWarning: use_inf_as_na option is deprecated and will be removed in a future version. Convert inf values to NaN before operating instead.\n", + " with pd.option_context('mode.use_inf_as_na', True):\n", + "/opt/anaconda3/lib/python3.11/site-packages/seaborn/_oldcore.py:1119: FutureWarning: use_inf_as_na option is deprecated and will be removed in a future version. Convert inf values to NaN before operating instead.\n", + " with pd.option_context('mode.use_inf_as_na', True):\n", + "/opt/anaconda3/lib/python3.11/site-packages/seaborn/_oldcore.py:1119: FutureWarning: use_inf_as_na option is deprecated and will be removed in a future version. Convert inf values to NaN before operating instead.\n", + " with pd.option_context('mode.use_inf_as_na', True):\n", + "/opt/anaconda3/lib/python3.11/site-packages/seaborn/_oldcore.py:1119: FutureWarning: use_inf_as_na option is deprecated and will be removed in a future version. Convert inf values to NaN before operating instead.\n", + " with pd.option_context('mode.use_inf_as_na', True):\n", + "/opt/anaconda3/lib/python3.11/site-packages/seaborn/_oldcore.py:1119: FutureWarning: use_inf_as_na option is deprecated and will be removed in a future version. Convert inf values to NaN before operating instead.\n", + " with pd.option_context('mode.use_inf_as_na', True):\n", + "/opt/anaconda3/lib/python3.11/site-packages/seaborn/_oldcore.py:1119: FutureWarning: use_inf_as_na option is deprecated and will be removed in a future version. Convert inf values to NaN before operating instead.\n", + " with pd.option_context('mode.use_inf_as_na', True):\n", + "/opt/anaconda3/lib/python3.11/site-packages/seaborn/_oldcore.py:1119: FutureWarning: use_inf_as_na option is deprecated and will be removed in a future version. Convert inf values to NaN before operating instead.\n", + " with pd.option_context('mode.use_inf_as_na', True):\n" + ] + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Scatter matrix of features\n", + "sns.pairplot(data_cleaned, diag_kind=\"kde\", corner=True, plot_kws={\"alpha\": 0.6})\n", + "plt.suptitle(\"Relationships Between Player Statistics and Points Scored\", y=1.02)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 758 + }, + "id": "iUotF0t8XUKo", + "outputId": "5e73e4ff-6475-4f32-9e44-106646357f35" + }, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Radar Chart: Key Skills of a Top Scorer vs. Team Average\n", + "\n", + "team_avg = data_cleaned[features].mean()\n", + "\n", + "\n", + "top_scorer_idx = data_cleaned['PTS'].idxmax()\n", + "top_scorer_stats = data_cleaned.loc[top_scorer_idx, features]\n", + "\n", + "categories = features\n", + "num_vars = len(categories)\n", + "\n", + "angles = [n / float(num_vars) * 2 * pi for n in range(num_vars)]\n", + "angles += angles[:1]\n", + "\n", + "team_avg_values = team_avg.tolist()\n", + "team_avg_values += team_avg_values[:1]\n", + "\n", + "top_scorer_values = top_scorer_stats.tolist()\n", + "top_scorer_values += top_scorer_values[:1]\n", + "\n", + "# Create radar chart\n", + "fig, ax = plt.subplots(figsize=(8, 8), subplot_kw=dict(polar=True))\n", + "ax.plot(angles, team_avg_values, linewidth=2, linestyle='solid', label=\"Team Average\")\n", + "ax.fill(angles, team_avg_values, alpha=0.25)\n", + "\n", + "ax.plot(angles, top_scorer_values, linewidth=2, linestyle='solid', label=\"Top Scorer\")\n", + "ax.fill(angles, top_scorer_values, alpha=0.25)\n", + "\n", + "ax.set_yticks([])\n", + "ax.set_xticks(angles[:-1])\n", + "ax.set_xticklabels(categories)\n", + "ax.set_title(\"Comparison of Key Skills: Top Scorer vs. Team Average\", y=1.1)\n", + "ax.legend(loc=\"upper right\")\n", + "plt.show()" + ] + } + ], + "metadata": { + "colab": { + "provenance": [] + }, + "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": "3.11.7" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/README.md b/README.md index f746e56..4f41b77 100644 --- a/README.md +++ b/README.md @@ -1,29 +1,311 @@ -# Project 2 +# **Volleyball Player Statistics Analysis for NCAA Division 3 (2024)** -Select one of the following two options: +--- -## Boosting Trees +### **Overview** -Implement the gradient-boosting tree algorithm (with the usual fit-predict interface) as described in Sections 10.9-10.10 of Elements of Statistical Learning (2nd Edition). Answer the questions below as you did for Project 1. +**PR Name**: *"Analysis of Volleyball Player Performance Metrics Using Machine Learning Techniques"* -Put your README below. Answer the following questions. +This project analyzes player statistics from the Illinois Tech volleyball team for NCAA Division 3 (2024). Using advanced machine learning techniques, the analysis evaluates the relationship between various player performance metrics and total points scored (`PTS`). The implementation focuses on model selection techniques such as **k-Fold Cross-Validation** and **Bootstrap .632**, alongside interpretive data visualizations to provide insights into player performance. -* What does the model you have implemented do and when should it be used? -* How did you test your model to determine if it is working reasonably correctly? -* What parameters have you exposed to users of your implementation in order to tune performance? (Also perhaps provide some basic usage examples.) -* Are there specific inputs that your implementation has trouble with? Given more time, could you work around these or is it fundamental? +--- -## Model Selection +### **How to Run the Code** -Implement generic k-fold cross-validation and bootstrapping model selection methods. +1. **Prepare the Required Files**: + - Download the `.ipynb` file containing the code. + - Download the dataset file (`tabula-mvb_stats_2024.csv`). -In your README, answer the following questions: +2. **Upload Files to Google Colab**: + - Open [Google Colab](https://colab.research.google.com/). + - Upload both the `.ipynb` file and the dataset file by clicking on the folder icon in the left sidebar and then the upload button. -* Do your cross-validation and bootstrapping model selectors agree with a simpler model selector like AIC in simple cases (like linear regression)? -* In what cases might the methods you've written fail or give incorrect or undesirable results? -* What could you implement given more time to mitigate these cases or help users of your methods? -* What parameters have you exposed to your users in order to use your model selectors. +3. **Set the Dataset Path**: + - After uploading, copy the file path for the dataset from the Colab file manager (e.g., `/content/tabula-mvb_stats_2024.csv`). + - Replace the `file_path` variable in the code with the copied path: + ```python + file_path = '/content/tabula-mvb_stats_2024.csv' + ``` -See sections 7.10-7.11 of Elements of Statistical Learning and the lecture notes. Pay particular attention to Section 7.10.2. +4. **Install Missing Libraries (If Any)**: + - If the code encounters a missing library error, install it by running: + ```python + !pip install + ``` + - Replace `` with the name of the required library (e.g., `seaborn`, `scikit-learn`, etc.). -As usual, above-and-beyond efforts will be considered for bonus points. +5. **Execute the Notebook**: + - Run the cells sequentially in Google Colab. + - Ensure that the dataset path is correctly set before running the code to avoid errors. + +6. **View the Results**: + - The outputs, including model evaluation metrics and visualizations, will be displayed in the Colab notebook. + +**Note**: The code has been optimized for **Google Colab**. Running it in other IDEs, such as Visual Studio Code, may result in incomplete visual outputs (e.g., heatmaps). Always use Google Colab for consistent and accurate results. + +--- + + +## **Implementation Details** + +### **1. Preprocessing** +- **Data Cleaning**: + - Handled missing values and clipped outliers using the 1st and 99th percentiles to ensure robust model performance. +- **Scaling**: + - Applied `RobustScaler` for effective handling of outliers during feature standardization. +- **Validation**: + - Verified the absence of `NaN` values in the feature matrix (`X`) and target vector (`y`) before and after preprocessing. + +--- + +### **2. Model Selection Techniques** + +#### **k-Fold Cross-Validation** +- **Description**: + - Splits the data into 5 folds, training on 4 and testing on 1 iteratively, to evaluate the model's generalization error. + - Calculates the Mean Squared Error (MSE) across all folds. +- **Output**: + - **k-Fold Cross-Validation MSE**: `3231.9376` +- **Interpretation**: + - This MSE indicates the model's average squared error on unseen data. A lower value suggests better generalization to new samples. + +--- + +#### **Bootstrap .632** +- **Description**: + - Resamples the dataset with replacement for training, while using out-of-bag samples for validation. + - Combines in-sample and out-of-sample errors using the `.632 adjustment` for a balanced error estimate. +- **Output**: + - **Bootstrap .632 MSE**: `1464.9683` +- **Interpretation**: + - The lower MSE compared to k-fold suggests potential overfitting, as the bootstrap error partially relies on in-sample performance. + +--- + +### **3. Model Accuracy** + +#### **R² Score** +- **Output**: `0.9995` +- **Description**: + - Measures how well the model explains the variability in the target variable (`PTS`). +- **Interpretation**: + - A value of **0.9995** indicates that the model explains **99.95% of the variance** in `PTS`, demonstrating an excellent fit. +- **Implications**: + - While predictions align closely with actual values, this high value might suggest **overfitting**, especially in small datasets. + +--- + +#### **Mean Absolute Error (MAE)** +- **Output**: `1.7995` +- **Description**: + - Measures the average absolute deviation between the predicted and actual points scored. +- **Interpretation**: + - The model's predictions are off by **1.7995 points** on average. For example, if a player scores 25 points, the model might predict **23.2 or 26.8**. +- **Implications**: + - A low MAE indicates strong predictive accuracy. + +--- + +## **Visualizations** + +### **1. Correlation Heatmap** +- **What It Shows**: + - Displays the relationships between performance metrics (e.g., `K`, `DIG`) and `PTS`. +- **Insights**: + - Metrics like `K` (Kills) and `K/S` (Kills per set) are strongly correlated with `PTS`, making them significant predictors of scoring. + +--- + +### **2. Learning Curve** +- **What It Shows**: + - Training and validation errors as a function of dataset size. +- **Insights**: + - Validation error stabilizes with more data, confirming the model's ability to generalize. + +--- + +### **3. Bias-Variance Trade-Off** +- **What It Shows**: + - The impact of model complexity (polynomial degree) on training and validation errors. +- **Insights**: + - Overfitting becomes apparent at higher degrees, as training error decreases but validation error increases. + +--- + +### **4. Residual Plot** +- **What It Shows**: + - Plots residuals (difference between predicted and actual `PTS`) against predicted values. +- **Insights**: + - A random scatter of residuals around 0 suggests the model is well-calibrated. + +--- + +### **5. Feature Importance** +- **What It Shows**: + - The contribution of each feature to predicting `PTS`. +- **Insights**: + - Features like `K` and `K/S` are the most significant, confirming their importance in scoring performance. + +--- + +### **6. Player Points Distribution** +- **What It Shows**: + - A histogram showing the distribution of `PTS` across all players. +- **Insights**: + - Highlights players with significantly higher scores, identifying outliers in performance. + +--- + +### **7. ROC Curve** +- **What It Shows**: + - Evaluates the model’s ability to classify players scoring above or below the average `PTS`. +- **Output**: + - **AUC**: `0.98` (excellent discrimination). +- **Insights**: + - The model effectively distinguishes high-scoring players from others. + +--- + +### **8. Radar Chart** +- **What It Shows**: + - Compares the top scorer’s performance metrics to the team average. +- **Insights**: + - Highlights areas where the top scorer excels, such as `Kills` and `Blocks`. + +--- + +## **Team Contributions** + +### **Kunal Nilesh Samant (20541900)** +- Implemented data preprocessing, including handling missing values, scaling, and clipping outliers. +- Developed the **k-Fold Cross-Validation** method with robust preprocessing in each fold. +- Created visualizations such as the **Correlation Heatmap**, **Feature Importance Bar Plot**, and **Residual Plot**. +- Provided interpretations for cross-validation results and feature importance. + +--- + +### **Dhruv Singh (A20541901)** +- Implemented the **Bootstrap .632 Estimator** with error handling. +- Added advanced visualizations, including the **Learning Curve**, **Bias-Variance Trade-Off**, and **Radar Chart**. +- Created and analyzed the **ROC Curve** for binary classification of player performance. +- Contributed detailed insights into numerical outputs like **R² Score**, **MAE**, and other model metrics. + + +--- +# **Project 2 Questions Answered** + +--- + +## **1. Do your cross-validation and bootstrapping model selectors agree with a simpler model selector like AIC in simple cases (like linear regression)?** + +In simple cases like linear regression, **cross-validation (k-fold)** and **bootstrap .632** generally align with simpler model selectors like the Akaike Information Criterion (AIC). AIC balances the model's goodness of fit with its complexity, penalizing models with excessive parameters, while cross-validation estimates the generalization error directly. Bootstrap .632 combines in-sample and out-of-sample errors to provide a robust estimate. + +In this dataset, the high **R² score (0.9995)** and low **MAE (1.7995)** indicate that the linear regression model fits exceptionally well, capturing almost all variance in the target (`PTS`). Both **k-fold MSE (3231.9376)** and **bootstrap .632 MSE (1464.9683)** suggest the model generalizes well, consistent with AIC’s preference for simpler models. + +However, differences may arise in more complex scenarios. For example, AIC assumes residual normality, which cross-validation and bootstrap do not. In this relatively small and clean dataset, these methods align well. + +--- + +## **2. In what cases might the methods you've written fail or give incorrect or undesirable results?** + +While cross-validation and bootstrap are robust, certain limitations can lead to failure or undesirable outcomes: + +### **Small Dataset** +With only 15 players, splitting into 5 folds leaves just 12 samples for training in each fold. This small size can limit the model's ability to generalize. Similarly, bootstrap resampling may repeatedly select similar subsets, reducing variability in error estimates. + +### **Overfitting** +The extremely high **R² score** suggests potential overfitting, where the model captures noise alongside actual relationships in the data. Bootstrap, which incorporates in-sample error, might underestimate the degree of overfitting. + +### **Outliers** +Despite clipping extreme values, residual outliers may distort predictions. For example, a player with unusually high stats could heavily influence the model’s parameters, inflating the MSE. + +### **Multicollinearity** +Features like `K` (Kills) and `K/S` (Kills per set) are highly correlated, causing multicollinearity. This can destabilize parameter estimation and inflate bootstrap variance. + +### **Misaligned Metrics** +Cross-validation minimizes MSE but doesn’t directly penalize model complexity. AIC accounts for complexity, but cross-validation might favor overly complex models in small datasets. + +--- + +## **3. What could you implement given more time to mitigate these cases or help users of your methods?** + +To address these challenges, the following improvements could be implemented: + +### **Regularization** +Introduce techniques like Ridge or Lasso regression to handle multicollinearity and reduce overfitting by penalizing large coefficients. + +### **Robust Preprocessing** +- Add automated outlier detection mechanisms to handle anomalies more effectively. +- Use feature engineering methods like **Principal Component Analysis (PCA)** to address multicollinearity. + +### **Hybrid Model Selection** +Combine AIC and cross-validation to balance goodness of fit with model complexity, leveraging AIC's simplicity criterion alongside empirical validation from cross-validation. + +### **Advanced Bootstrap Techniques** +Implement alternative methods such as **balanced bootstrap**, which ensures diverse resampling, improving error variability estimates for small datasets. + +### **Visualization Tools** +Expand diagnostic visualizations (e.g., residual plots, learning curves, bias-variance trade-off) to provide users with a deeper understanding of model performance and limitations. + +### **Exposed Parameters** +Expose fine-tuning parameters for users, such as: +- Number of folds in cross-validation. +- Number of bootstrap iterations. +- Gradient descent hyperparameters (learning rate, iterations). +- Preprocessing thresholds for outlier clipping. + +--- + +## **4. What parameters have you exposed to your users in order to use your model selectors?** + +### **Cross-Validation** +- `k`: Number of folds (default: 5). +- `shuffle`: Whether to shuffle the data before splitting. +- `random_state`: Seed for reproducibility. + +### **Bootstrap** +- `n_iterations`: Number of bootstrap samples (default: 100). +- `.632 adjustment`: Balances in-sample and out-of-bag errors. + +### **Gradient Descent** +- `alpha`: Learning rate (default: 0.01). +- `iterations`: Number of iterations for convergence (default: 1000). +- `clip_value`: Threshold for gradient clipping to stabilize updates. + +### **Preprocessing** +- Outlier clipping thresholds (1st and 99th percentiles). +- Scaling method (`RobustScaler`) for handling skewness and outliers. + +### **Model Evaluation** +- Metrics: **MSE**, **R² score**, **MAE**, and **ROC-AUC** for comprehensive performance assessment. + +--- + +## **Output Interpretation** + +### **k-Fold Cross-Validation MSE**: `3231.9376` +- **What it Means**: + - Reflects the average squared error on unseen data. A lower value indicates better generalization. +- **Implication**: + - The model performs well on unseen data but shows some error variability. + +### **Bootstrap .632 MSE**: `1464.9683` +- **What it Means**: + - Provides a slightly optimistic error estimate by blending in-sample and out-of-sample errors. +- **Implication**: + - A lower error compared to k-fold suggests some overfitting to the training data. + +### **R² Score**: `0.9995` +- **What it Means**: + - Explains **99.95% of the variability** in `PTS`. Indicates an excellent model fit. +- **Implication**: + - Highlights strong predictive accuracy but raises concerns about overfitting. + +### **MAE**: `1.7995` +- **What it Means**: + - Average deviation of predictions from actual values is **1.8 points**. + - For instance, if a player scores 25 points, the model might predict **23.2 or 26.8**. +- **Implication**: + - Low MAE indicates good predictive precision, acceptable in this context. + +--- diff --git a/tabula-mvb_stats_2024.csv b/tabula-mvb_stats_2024.csv new file mode 100644 index 0000000..a679295 --- /dev/null +++ b/tabula-mvb_stats_2024.csv @@ -0,0 +1,14 @@ +"#",Player,SP,K,K/S,E,TA,Pct,A,A/S,SA,SE,SA/S,RE,DIG,DIG/S,BS,BA,BLK,BLK/S,BE,BHE,PTS +2,"Johnson, Elijah",85,20,0.24,7,103,.126,634,7.46,11,32,0.13,1,161,1.89,2,21,23.0,0.27,12,3,43.5 +4,"Donald, Alec",97,0,0.00,5,33,-.152,50,0.52,0,0,0.00,15,279,2.88,0,1,1.0,0.01,0,1,0.5 +5,"Baus, Zachary",48,0,0.00,0,1,.000,2,0.04,0,0,0.00,2,25,0.52,0,0,0,0.00,0,2,0 +6,"Henderson, Paul",88,131,1.49,76,460,.120,13,0.15,26,47,0.30,4,185,2.10,8,20,28.0,0.32,14,1,175.0 +7,"Singer, David",51,83,1.63,54,237,.122,5,0.10,3,27,0.06,4,57,1.12,3,10,13.0,0.25,9,0,94.0 +8,"Hanny, Aaron",27,34,1.26,25,92,.098,6,0.22,4,16,0.15,0,19,0.70,0,12,12.0,0.44,6,1,44.0 +9,"Couper, Grant",90,223,2.48,108,675,.170,10,0.11,17,50,0.19,13,174,1.93,8,18,26.0,0.29,14,0,257.0 +10,"Evans, Bryan",27,28,1.04,19,80,.113,1,0.04,0,3,0.00,6,19,0.70,2,2,4.0,0.15,5,0,31.0 +11,"Sherman, Eli",57,22,0.39,4,63,.286,256,4.49,9,12,0.16,0,43,0.75,1,6,7.0,0.12,3,3,35.0 +13,"Van Engen, Jackson",99,232,2.34,68,482,.340,12,0.12,23,69,0.23,0,77,0.78,29,50,79.0,0.80,31,1,309.0 +14,"Laite, Riley",85,218,2.56,120,559,.175,6,0.07,17,65,0.20,13,160,1.88,4,10,14.0,0.16,15,0,244.0 +24,"Kimoto, Jelani",72,61,0.85,35,199,.131,4,0.06,3,11,0.04,0,44,0.61,10,38,48.0,0.67,26,2,93.0 +25,"Farrell, Colten",32,29,0.91,11,72,.250,0,0.00,4,7,0.13,1,17,0.53,2,12,14.0,0.44,14,0,41.0