{
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "# Import Necessary Libraries"
      ],
      "metadata": {
        "id": "kE4HTLBolr8k"
      },
      "id": "kE4HTLBolr8k"
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "id": "f2641c20",
      "metadata": {
        "id": "f2641c20"
      },
      "outputs": [],
      "source": [
        "from sklearn.linear_model import LinearRegression\n",
        "import os\n",
        "import sys\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import statsmodels\n",
        "import statsmodels.api as sm\n",
        "import statsmodels.formula.api as smf\n",
        "import matplotlib\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "from sklearn.model_selection import train_test_split, StratifiedKFold\n",
        "from sklearn.utils import shuffle\n",
        "import scipy.stats as stats\n",
        "from sklearn.ensemble import AdaBoostClassifier\n",
        "from sklearn.tree import DecisionTreeClassifier\n",
        "from sklearn.metrics import accuracy_score\n",
        "from sklearn.compose import ColumnTransformer\n",
        "from sklearn.pipeline import Pipeline\n",
        "from scipy.stats import pearsonr\n",
        "from sklearn.preprocessing import StandardScaler, OneHotEncoder, OrdinalEncoder\n",
        "import zipfile\n",
        "import io\n",
        "from io import StringIO\n",
        "import requests"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "ADCmFcuQyZuu",
      "metadata": {
        "id": "ADCmFcuQyZuu"
      },
      "source": [
        "# **Introduction and Motivation**\n",
        "### Upon running cross-validation of AdaBoost on 'adult' census data sorced from UCI's Machine Learning data repository, we discovered an anticorrelation phenomena in the training and test error rates.\n",
        "\n",
        "### We continued to explore this phenomena by running Adaboost CV trials on other sets from UCI's website. Detailed below; what we saw was a pattern detailed in our paper's model. CV run on larger samples and data that was too easy or difficult would lose this anti-correlation effect.\n",
        "\n",
        "### We also tried to run the experiment on synthetic data to see if this correlation would still exist and if it would confirm our results.\n",
        "\n",
        "### To keep things consistent we always use 50 estimators in our Adaboost model. We also fix the partition of Holdout/Test/Train to be 10% of data first taken as a Holdout set, then 25% of the remaining portion is the Test set and the rest is the Training set.\n"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# UCI Adult Data Set\n",
        "\n",
        "#### The Adult data set takes attributes from the census data and aims to classify people as making less than \\$50k/yr or more than $50k/yr. We download the set directly from UCI to keep everything contained in this notebook, then preprocess the data to run SkLearn's Adaboost function on the data and run 100 trials of cross validation. This procedure is replicated for all data sets run.\n",
        "\n",
        "## Relevant Feature Info\n",
        "\n",
        "#### - Binary Classification\n",
        "#### - Large data size >48k instances\n",
        "#### - 14 features"
      ],
      "metadata": {
        "id": "lHdmDtQyjNDQ"
      },
      "id": "lHdmDtQyjNDQ"
    },
    {
      "cell_type": "code",
      "source": [
        "# Download and load the UCI Adult dataset\n",
        "def load_adult_data():\n",
        "    \"\"\"\n",
        "    Download and prepare the UCI Adult dataset\n",
        "    \"\"\"\n",
        "    # URLs for the Adult dataset\n",
        "    train_url = \"https://archive.ics.uci.edu/ml/machine-learning-databases/adult/adult.data\"\n",
        "    test_url = \"https://archive.ics.uci.edu/ml/machine-learning-databases/adult/adult.test\"\n",
        "\n",
        "    # Column names for the dataset\n",
        "    column_names = [\n",
        "        'age', 'workclass', 'fnlwgt', 'education', 'education-num',\n",
        "        'marital-status', 'occupation', 'relationship', 'race', 'sex',\n",
        "        'capital-gain', 'capital-loss', 'hours-per-week', 'native-country', 'income'\n",
        "    ]\n",
        "\n",
        "    # Load the data\n",
        "    train_data = pd.read_csv(train_url, names=column_names, sep=', ', engine='python')\n",
        "    test_data = pd.read_csv(test_url, names=column_names, sep=', ', engine='python', skiprows=1)\n",
        "\n",
        "    # Fix the income column in test set (remove the trailing dot)\n",
        "    test_data['income'] = test_data['income'].str.rstrip('.')\n",
        "\n",
        "    # Combine the datasets\n",
        "    all_data = pd.concat([train_data, test_data])\n",
        "\n",
        "    # Map the target variable to binary\n",
        "    all_data['income'] = all_data['income'].map({'<=50K': 0, '>50K': 1, '<=50K.': 0, '>50K.': 1})\n",
        "\n",
        "    return all_data\n",
        "\n",
        "# Function to preprocess the Adult dataset\n",
        "def preprocess_adult_data(data):\n",
        "    \"\"\"\n",
        "    Preprocess the Adult dataset for machine learning\n",
        "    \"\"\"\n",
        "    # Drop rows with missing values for simplicity\n",
        "    data = data.replace('?', np.nan).dropna()\n",
        "\n",
        "    # Split features and target\n",
        "    X = data.drop('income', axis=1)\n",
        "    y = data['income']\n",
        "\n",
        "    # Identify numeric and categorical columns\n",
        "    numeric_features = X.select_dtypes(include=['int64', 'float64']).columns\n",
        "    categorical_features = X.select_dtypes(include=['object']).columns\n",
        "\n",
        "    # Define preprocessing for numerical and categorical features\n",
        "    numeric_transformer = StandardScaler()\n",
        "    categorical_transformer = OneHotEncoder(handle_unknown='ignore')\n",
        "\n",
        "    # Create preprocessing steps\n",
        "    preprocessor = ColumnTransformer(\n",
        "        transformers=[\n",
        "            ('num', numeric_transformer, numeric_features),\n",
        "            ('cat', categorical_transformer, categorical_features)\n",
        "        ])\n",
        "\n",
        "    return X, y, preprocessor\n",
        "\n",
        "# Run the AdaBoost cross-validation experiment\n",
        "def run_adaboost_experiment(X, y, preprocessor, n_runs=100):\n",
        "    \"\"\"\n",
        "    Run the AdaBoost experiment with the same setup as the synthetic data experiment\n",
        "    \"\"\"\n",
        "    # Base learner: decision stump (depth-1 decision tree)\n",
        "    base_learner = DecisionTreeClassifier(max_depth=1)\n",
        "\n",
        "    adult = []\n",
        "\n",
        "    for seed in range(n_runs):\n",
        "        # Split into train-val and holdout sets\n",
        "        X_train_val, X_holdout, y_train_val, y_holdout = train_test_split(\n",
        "            X, y, test_size=0.1, random_state=seed, stratify=y)\n",
        "\n",
        "        # Further split train-val into train and test\n",
        "        X_train, X_test, y_train, y_test = train_test_split(\n",
        "            X_train_val, y_train_val, test_size=0.25, random_state=seed, stratify=y_train_val)\n",
        "\n",
        "        # Create and train the pipeline\n",
        "        pipeline = Pipeline([\n",
        "            ('preprocessor', preprocessor),\n",
        "            ('classifier', AdaBoostClassifier(\n",
        "                estimator=base_learner,\n",
        "                n_estimators=50,\n",
        "                random_state=seed))\n",
        "        ])\n",
        "\n",
        "        pipeline.fit(X_train, y_train)\n",
        "\n",
        "        # Calculate errors\n",
        "        train_error = 1 - accuracy_score(y_train, pipeline.predict(X_train))\n",
        "        test_error = 1 - accuracy_score(y_test, pipeline.predict(X_test))\n",
        "        holdout_error = 1 - accuracy_score(y_holdout, pipeline.predict(X_holdout))\n",
        "\n",
        "        adult.append({\n",
        "            'seed': seed,\n",
        "            'Training Error': train_error,\n",
        "            'Test Error': test_error,\n",
        "            'Holdout Error': holdout_error\n",
        "        })\n",
        "\n",
        "    return pd.DataFrame(adult)\n",
        "\n",
        "# Load and prepare the data\n",
        "adult_data = load_adult_data()\n",
        "print(f\"Dataset shape: {adult_data.shape}\")\n",
        "\n",
        "# Sample the data to speed up computation (optional)\n",
        "# Comment out this line for full dataset\n",
        "#adult_data = adult_data.sample(n=5000, random_state=42)\n",
        "\n",
        "# Preprocess the data\n",
        "X, y, preprocessor = preprocess_adult_data(adult_data)\n",
        "\n",
        "# Run the experiment\n",
        "adult_df = run_adaboost_experiment(X, y, preprocessor, n_runs=100)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0AA6qeNVriXW",
        "outputId": "8e8c7b91-5f87-4e7c-aa94-331f867c61fa"
      },
      "id": "0AA6qeNVriXW",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Dataset shape: (48842, 15)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Visualization of UCI Adult data"
      ],
      "metadata": {
        "id": "td8DE-6zl3zT"
      },
      "id": "td8DE-6zl3zT"
    },
    {
      "cell_type": "code",
      "source": [
        "# Step 8: Set figure size for a row of 3 plots\n",
        "plt.figure(figsize=(18, 5))\n",
        "\n",
        "# Define custom colors\n",
        "custom_colors = [\"#2ecc71\",  # Green\n",
        "                 \"#e74c3c\",  # Red\n",
        "                 \"#3498db\",  # Blue\n",
        "                 \"#9b59b6\"]  # Purple\n",
        "sns.set_palette(custom_colors)\n",
        "\n",
        "# First plot: Training vs Test Error\n",
        "plt.subplot(1, 3, 1)\n",
        "# Calculate correlation coefficient (R) and p-value\n",
        "r_train_test, p_train_test = stats.pearsonr(adult_df['Training Error'], adult_df['Test Error'])\n",
        "r2_train_test = r_train_test**2\n",
        "# Add regression plot\n",
        "sns.regplot(data=adult_df, x='Training Error', y='Test Error',\n",
        "            scatter_kws={'color': custom_colors[0]},\n",
        "            line_kws={'color': custom_colors[0], 'linewidth': 2})\n",
        "# Add R and R² text\n",
        "plt.annotate(f'r = {r_train_test:.3f}\\nr² = {r2_train_test:.3f}',\n",
        "             xy=(0.05, 0.90), xycoords='axes fraction',\n",
        "             bbox=dict(boxstyle=\"round,pad=0.3\", fc=\"white\", ec=\"gray\", alpha=0.8))\n",
        "plt.title('Training vs. Test Error')\n",
        "plt.xlabel('Training Error')\n",
        "plt.ylabel('Test Error')\n",
        "\n",
        "# Second plot: Training vs Holdout Error\n",
        "plt.subplot(1, 3, 2)\n",
        "# Calculate correlation coefficient (R) and p-value\n",
        "r_train_holdout, p_train_holdout = stats.pearsonr(adult_df['Training Error'], adult_df['Holdout Error'])\n",
        "r2_train_holdout = r_train_holdout**2\n",
        "# Add regression plot\n",
        "sns.regplot(data=adult_df, x='Training Error', y='Holdout Error',\n",
        "            scatter_kws={'color': custom_colors[1]},\n",
        "            line_kws={'color': custom_colors[1], 'linewidth': 2})\n",
        "# Add R and R² text\n",
        "plt.annotate(f'r = {r_train_holdout:.3f}\\nr² = {r2_train_holdout:.3f}',\n",
        "             xy=(0.05, 0.90), xycoords='axes fraction',\n",
        "             bbox=dict(boxstyle=\"round,pad=0.3\", fc=\"white\", ec=\"gray\", alpha=0.8))\n",
        "plt.title('Training vs. Holdout Error')\n",
        "plt.xlabel('Training Error')\n",
        "plt.ylabel('Holdout Error')\n",
        "\n",
        "# Third plot: Test vs Holdout Error\n",
        "plt.subplot(1, 3, 3)\n",
        "# Calculate correlation coefficient (R) and p-value\n",
        "r_test_holdout, p_test_holdout = stats.pearsonr(adult_df['Test Error'], adult_df['Holdout Error'])\n",
        "r2_test_holdout = r_test_holdout**2\n",
        "# Add regression plot\n",
        "sns.regplot(data=adult_df, x='Test Error', y='Holdout Error',\n",
        "            scatter_kws={'color': custom_colors[2]},\n",
        "            line_kws={'color': custom_colors[2], 'linewidth': 2})\n",
        "# Add R and R² text\n",
        "plt.annotate(f'r = {r_test_holdout:.3f}\\nr² = {r2_test_holdout:.3f}',\n",
        "             xy=(0.05, 0.90), xycoords='axes fraction',\n",
        "             bbox=dict(boxstyle=\"round,pad=0.3\", fc=\"white\", ec=\"gray\", alpha=0.8))\n",
        "plt.title('Test vs. Holdout Error')\n",
        "plt.xlabel('Test Error')\n",
        "plt.ylabel('Holdout Error')\n",
        "\n",
        "# Adjust layout to prevent overlap\n",
        "plt.tight_layout()\n",
        "\n",
        "# Show the plots\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 376
        },
        "id": "rK9PEshStSg4",
        "outputId": "e6b8e160-0607-4d87-87d1-6d66091c169d"
      },
      "id": "rK9PEshStSg4",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1800x500 with 3 Axes>"
            ],
            "image/png": 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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Interpretation of Results (UCI Adult)\n",
        "\n",
        "#### Here we see the anti-correlation phenomena clearly present, despite the large data set we are processing; indicating that the α factor may be large to give this strong of an effect. We also see the secondary effect of mild effect of anti-correlation in the Training vs. Holdout plot, suggesting that this model is prone to overfitting."
      ],
      "metadata": {
        "id": "8V_SexUgmGVv"
      },
      "id": "8V_SexUgmGVv"
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Analysis of UCI Heart Disease\n",
        "\n",
        "#### Data set with features trying to predict whether or not a patient has heart disease or not. Same process as above for CV procedure.\n",
        "\n",
        "## Relevant Feature Info\n",
        "#### - Small Data set ~ 300 instances\n",
        "#### - Binary classification task (more susceptible to overfitting)\n",
        "#### - 73 features"
      ],
      "metadata": {
        "id": "yB_hA4FPoDwA"
      },
      "id": "yB_hA4FPoDwA"
    },
    {
      "cell_type": "code",
      "source": [
        "def load_heart_disease_data():\n",
        "    \"\"\"\n",
        "    Download and prepare the UCI Heart Disease dataset\n",
        "    \"\"\"\n",
        "    # URL for the Heart Disease dataset\n",
        "    url = \"https://archive.ics.uci.edu/ml/machine-learning-databases/heart-disease/processed.cleveland.data\"\n",
        "\n",
        "    # Column names for the dataset\n",
        "    column_names = [\n",
        "        'age', 'sex', 'cp', 'trestbps', 'chol', 'fbs', 'restecg',\n",
        "        'thalach', 'exang', 'oldpeak', 'slope', 'ca', 'thal', 'target'\n",
        "    ]\n",
        "\n",
        "    # Load the data\n",
        "    data = pd.read_csv(url, names=column_names, na_values='?')\n",
        "\n",
        "    # Convert the target column to binary (0 = no disease, 1 = disease)\n",
        "    # In the original data, 0 is no disease and 1-4 indicates disease of varying severity\n",
        "    data['target'] = data['target'].apply(lambda x: 0 if x == 0 else 1)\n",
        "\n",
        "    return data\n",
        "\n",
        "# Function to preprocess the Heart Disease dataset\n",
        "def preprocess_heart_data(data):\n",
        "    \"\"\"\n",
        "    Preprocess the Heart Disease dataset for machine learning\n",
        "    \"\"\"\n",
        "    # Drop rows with missing values for simplicity\n",
        "    data = data.dropna()\n",
        "\n",
        "    # Split features and target\n",
        "    X = data.drop('target', axis=1)\n",
        "    y = data['target']\n",
        "\n",
        "    # Identify numeric and categorical columns\n",
        "    # For the heart dataset, 'ca' and 'thal' are categorical despite being numeric\n",
        "    numeric_features = ['age', 'trestbps', 'chol', 'thalach', 'oldpeak']\n",
        "    categorical_features = ['sex', 'cp', 'fbs', 'restecg', 'exang', 'slope', 'ca', 'thal']\n",
        "\n",
        "    # Define preprocessing for numerical and categorical features\n",
        "    numeric_transformer = StandardScaler()\n",
        "    categorical_transformer = OneHotEncoder(handle_unknown='ignore')\n",
        "\n",
        "    # Create preprocessing steps\n",
        "    preprocessor = ColumnTransformer(\n",
        "        transformers=[\n",
        "            ('num', numeric_transformer, numeric_features),\n",
        "            ('cat', categorical_transformer, categorical_features)\n",
        "        ])\n",
        "\n",
        "    return X, y, preprocessor\n",
        "\n",
        "# Run the AdaBoost cross-validation experiment\n",
        "def run_adaboost_experiment(X, y, preprocessor, n_runs=100):\n",
        "    \"\"\"\n",
        "    Run the AdaBoost experiment with multiple train-test splits\n",
        "    \"\"\"\n",
        "    # Base learner: decision stump (depth-1 decision tree)\n",
        "    base_learner = DecisionTreeClassifier(max_depth=1)\n",
        "\n",
        "    results = []\n",
        "\n",
        "    for seed in range(n_runs):\n",
        "        # Split into train-val and holdout sets\n",
        "        X_train_val, X_holdout, y_train_val, y_holdout = train_test_split(\n",
        "            X, y, test_size=0.1, random_state=seed, stratify=y)\n",
        "\n",
        "        # Further split train-val into train and test\n",
        "        X_train, X_test, y_train, y_test = train_test_split(\n",
        "            X_train_val, y_train_val, test_size=0.25, random_state=seed, stratify=y_train_val)\n",
        "\n",
        "        # Create and train the pipeline\n",
        "        pipeline = Pipeline([\n",
        "            ('preprocessor', preprocessor),\n",
        "            ('classifier', AdaBoostClassifier(\n",
        "                estimator=base_learner,\n",
        "                n_estimators=50,\n",
        "                random_state=seed))\n",
        "        ])\n",
        "\n",
        "        pipeline.fit(X_train, y_train)\n",
        "\n",
        "        # Calculate errors\n",
        "        train_error = 1 - accuracy_score(y_train, pipeline.predict(X_train))\n",
        "        test_error = 1 - accuracy_score(y_test, pipeline.predict(X_test))\n",
        "        holdout_error = 1 - accuracy_score(y_holdout, pipeline.predict(X_holdout))\n",
        "\n",
        "        results.append({\n",
        "            'seed': seed,\n",
        "            'Training Error': train_error,\n",
        "            'Test Error': test_error,\n",
        "            'Holdout Error': holdout_error\n",
        "        })\n",
        "\n",
        "    return pd.DataFrame(results)\n",
        "\n",
        "\n",
        "\n",
        "# Main execution\n",
        "if __name__ == \"__main__\":\n",
        "    # Load and prepare the data\n",
        "    heart_data = load_heart_disease_data()\n",
        "    print(f\"Dataset shape: {heart_data.shape}\")\n",
        "\n",
        "    # Preprocess the data\n",
        "    X, y, preprocessor = preprocess_heart_data(heart_data)\n",
        "\n",
        "    # Run the experiment\n",
        "    heart_df = run_adaboost_experiment(X, y, preprocessor, n_runs=100)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WRm8wXyO0mOe",
        "outputId": "3ddcec48-7ed9-46dd-9086-2802c3f21c81"
      },
      "id": "WRm8wXyO0mOe",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Dataset shape: (303, 14)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Visualization of UCI Heart Disease"
      ],
      "metadata": {
        "id": "2k2eRrQxp1vi"
      },
      "id": "2k2eRrQxp1vi"
    },
    {
      "cell_type": "code",
      "source": [
        "# Step 8: Set figure size for a row of 3 plots\n",
        "plt.figure(figsize=(18, 5))\n",
        "\n",
        "# Define custom colors\n",
        "custom_colors = [\"#2ecc71\",  # Green\n",
        "                 \"#e74c3c\",  # Red\n",
        "                 \"#3498db\",  # Blue\n",
        "                 \"#9b59b6\"]  # Purple\n",
        "sns.set_palette(custom_colors)\n",
        "\n",
        "# First plot: Training vs Test Error\n",
        "plt.subplot(1, 3, 1)\n",
        "# Calculate correlation coefficient (R) and p-value\n",
        "r_train_test, p_train_test = stats.pearsonr(heart_df['Training Error'], heart_df['Test Error'])\n",
        "r2_train_test = r_train_test**2\n",
        "# Add regression plot\n",
        "sns.regplot(data=heart_df, x='Training Error', y='Test Error',\n",
        "            scatter_kws={'color': custom_colors[0]},\n",
        "            line_kws={'color': custom_colors[0], 'linewidth': 2})\n",
        "# Add R and R² text\n",
        "plt.annotate(f'r = {r_train_test:.3f}\\nr² = {r2_train_test:.3f}',\n",
        "             xy=(0.05, 0.90), xycoords='axes fraction',\n",
        "             bbox=dict(boxstyle=\"round,pad=0.3\", fc=\"white\", ec=\"gray\", alpha=0.8))\n",
        "plt.title('Training vs. Test Error')\n",
        "plt.xlabel('Training Error')\n",
        "plt.ylabel('Test Error')\n",
        "\n",
        "# Second plot: Training vs Holdout Error\n",
        "plt.subplot(1, 3, 2)\n",
        "# Calculate correlation coefficient (R) and p-value\n",
        "r_train_holdout, p_train_holdout = stats.pearsonr(heart_df['Training Error'], heart_df['Holdout Error'])\n",
        "r2_train_holdout = r_train_holdout**2\n",
        "# Add regression plot\n",
        "sns.regplot(data=heart_df, x='Training Error', y='Holdout Error',\n",
        "            scatter_kws={'color': custom_colors[1]},\n",
        "            line_kws={'color': custom_colors[1], 'linewidth': 2})\n",
        "# Add R and R² text\n",
        "plt.annotate(f'r = {r_train_holdout:.3f}\\nr² = {r2_train_holdout:.3f}',\n",
        "             xy=(0.05, 0.90), xycoords='axes fraction',\n",
        "             bbox=dict(boxstyle=\"round,pad=0.3\", fc=\"white\", ec=\"gray\", alpha=0.8))\n",
        "plt.title('Training vs. Holdout Error')\n",
        "plt.xlabel('Training Error')\n",
        "plt.ylabel('Holdout Error')\n",
        "\n",
        "# Third plot: Test vs Holdout Error\n",
        "plt.subplot(1, 3, 3)\n",
        "# Calculate correlation coefficient (R) and p-value\n",
        "r_test_holdout, p_test_holdout = stats.pearsonr(heart_df['Test Error'], heart_df['Holdout Error'])\n",
        "r2_test_holdout = r_test_holdout**2\n",
        "# Add regression plot\n",
        "sns.regplot(data=heart_df, x='Test Error', y='Holdout Error',\n",
        "            scatter_kws={'color': custom_colors[2]},\n",
        "            line_kws={'color': custom_colors[2], 'linewidth': 2})\n",
        "# Add R and R² text\n",
        "plt.annotate(f'r = {r_test_holdout:.3f}\\nr² = {r2_test_holdout:.3f}',\n",
        "             xy=(0.05, 0.90), xycoords='axes fraction',\n",
        "             bbox=dict(boxstyle=\"round,pad=0.3\", fc=\"white\", ec=\"gray\", alpha=0.8))\n",
        "plt.title('Test vs. Holdout Error')\n",
        "plt.xlabel('Test Error')\n",
        "plt.ylabel('Holdout Error')\n",
        "\n",
        "# Adjust layout to prevent overlap\n",
        "plt.tight_layout()\n",
        "\n",
        "# Show the plots\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 377
        },
        "id": "jOivQRZb1c8i",
        "outputId": "7c2840c0-a204-4afd-bac5-189fbb636bf3"
      },
      "id": "jOivQRZb1c8i",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1800x500 with 3 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Interpretation of Results (UCI Heart Disease)\n",
        "\n",
        "#### We see very similar results of overfitting as we did in the 'Adult' data set, but like we addressed earlier, this model is running on a smaller data set which we addressed should result in higher anticorrelation due to the $\\frac{1}{n(M-n)}$ factor in $\\mathrm{Cov}\\bigl(\\hat{p}_{\\rm train},\\hat{p}_{\\rm test}\\bigr)\n",
        "$. We do also see this grid-like quality to the distribution of error points, which may also be due to the small sample size."
      ],
      "metadata": {
        "id": "LGsZmZ2Ip9rh"
      },
      "id": "LGsZmZ2Ip9rh"
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Analysis of UCI Bank Marketing Data\n",
        "\n",
        "#### This data is from a Portugeuse bank tracking whether a client will subscribe a term deposit. Processed with the same procedure.\n",
        "\n",
        "## Relevant Features\n",
        "\n",
        "#### - Binary Target\n",
        "#### - Medium size dataset (~4k)\n",
        "#### - 16 Features\n",
        "\n"
      ],
      "metadata": {
        "id": "eG0nM2Lfz9Gp"
      },
      "id": "eG0nM2Lfz9Gp"
    },
    {
      "cell_type": "code",
      "source": [
        "def load_bank_marketing_data():\n",
        "    \"\"\"\n",
        "    Load the Bank Marketing dataset from a ZIP archive hosted on UCI\n",
        "    \"\"\"\n",
        "    url = \"https://archive.ics.uci.edu/ml/machine-learning-databases/00222/bank.zip\"\n",
        "    response = requests.get(url)\n",
        "    with zipfile.ZipFile(io.BytesIO(response.content)) as z:\n",
        "        with z.open(\"bank.csv\") as f:\n",
        "            data = pd.read_csv(f, sep=';')\n",
        "\n",
        "    # Convert the target variable to binary\n",
        "    data['y'] = data['y'].map({'yes': 1, 'no': 0})\n",
        "\n",
        "    return data\n",
        "def preprocess_bank_data(data):\n",
        "    \"\"\"\n",
        "    Preprocess the Bank Marketing dataset for machine learning\n",
        "    \"\"\"\n",
        "    # Split features and target\n",
        "    X = data.drop('y', axis=1)\n",
        "    y = data['y']\n",
        "\n",
        "    # Identify categorical and numerical columns\n",
        "    numeric_features = X.select_dtypes(include=['int64', 'float64']).columns.tolist()\n",
        "    categorical_features = X.select_dtypes(include=['object']).columns.tolist()\n",
        "\n",
        "    # Define transformers\n",
        "    numeric_transformer = StandardScaler()\n",
        "    categorical_transformer = OneHotEncoder(handle_unknown='ignore')\n",
        "\n",
        "    # Create ColumnTransformer\n",
        "    preprocessor = ColumnTransformer(\n",
        "        transformers=[\n",
        "            ('num', numeric_transformer, numeric_features),\n",
        "            ('cat', categorical_transformer, categorical_features)\n",
        "        ])\n",
        "\n",
        "    return X, y, preprocessor\n",
        "\n",
        "\n",
        "# Run the AdaBoost cross-validation experiment\n",
        "def run_adaboost_experiment(X, y, preprocessor, n_runs=100):\n",
        "    \"\"\"\n",
        "    Run the AdaBoost experiment with multiple train-test splits\n",
        "    \"\"\"\n",
        "    # Base learner: decision stump (depth-1 decision tree)\n",
        "    base_learner = DecisionTreeClassifier(max_depth=1)\n",
        "\n",
        "    results = []\n",
        "\n",
        "    for seed in range(n_runs):\n",
        "        # Split into train-val and holdout sets\n",
        "        X_train_val, X_holdout, y_train_val, y_holdout = train_test_split(\n",
        "            X, y, test_size=0.1, random_state=seed, stratify=y)\n",
        "\n",
        "        # Further split train-val into train and test\n",
        "        X_train, X_test, y_train, y_test = train_test_split(\n",
        "            X_train_val, y_train_val, test_size=0.25, random_state=seed, stratify=y_train_val)\n",
        "\n",
        "        # Create and train the pipeline\n",
        "        pipeline = Pipeline([\n",
        "            ('preprocessor', preprocessor),\n",
        "            ('classifier', AdaBoostClassifier(\n",
        "                estimator=base_learner,\n",
        "                n_estimators=50,\n",
        "                random_state=seed))\n",
        "        ])\n",
        "\n",
        "        pipeline.fit(X_train, y_train)\n",
        "\n",
        "        # Calculate errors\n",
        "        train_error = 1 - accuracy_score(y_train, pipeline.predict(X_train))\n",
        "        test_error = 1 - accuracy_score(y_test, pipeline.predict(X_test))\n",
        "        holdout_error = 1 - accuracy_score(y_holdout, pipeline.predict(X_holdout))\n",
        "\n",
        "        results.append({\n",
        "            'seed': seed,\n",
        "            'Training Error': train_error,\n",
        "            'Test Error': test_error,\n",
        "            'Holdout Error': holdout_error\n",
        "        })\n",
        "\n",
        "    return pd.DataFrame(results)\n",
        "\n",
        "\n",
        "\n",
        "if __name__ == \"__main__\":\n",
        "    # Load and prepare the data\n",
        "    bank_data = load_bank_marketing_data()\n",
        "    print(f\"Dataset shape: {bank_data.shape}\")\n",
        "\n",
        "    # Preprocess the data\n",
        "    X, y, preprocessor = preprocess_bank_data(bank_data)\n",
        "\n",
        "    # Run the experiment\n",
        "    bank_results_df = run_adaboost_experiment(X, y, preprocessor, n_runs=100)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Am6BntHf_Wjw",
        "outputId": "b199447e-bd3d-47f7-c38f-b9578e010465"
      },
      "id": "Am6BntHf_Wjw",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Dataset shape: (4521, 17)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Visulazation of UCI Bank Marketing"
      ],
      "metadata": {
        "id": "Nh3EcNkm1CP7"
      },
      "id": "Nh3EcNkm1CP7"
    },
    {
      "cell_type": "code",
      "source": [
        "# Step 8: Set figure size for a row of 3 plots\n",
        "plt.figure(figsize=(18, 5))\n",
        "\n",
        "# Define custom colors\n",
        "custom_colors = [\"#2ecc71\",  # Green\n",
        "                 \"#e74c3c\",  # Red\n",
        "                 \"#3498db\",  # Blue\n",
        "                 \"#9b59b6\"]  # Purple\n",
        "sns.set_palette(custom_colors)\n",
        "\n",
        "# First plot: Training vs Test Error\n",
        "plt.subplot(1, 3, 1)\n",
        "# Calculate correlation coefficient (R) and p-value\n",
        "r_train_test, p_train_test = stats.pearsonr(bank_results_df['Training Error'], bank_results_df['Test Error'])\n",
        "r2_train_test = r_train_test**2\n",
        "# Add regression plot\n",
        "sns.regplot(data=bank_results_df, x='Training Error', y='Test Error',\n",
        "            scatter_kws={'color': custom_colors[0]},\n",
        "            line_kws={'color': custom_colors[0], 'linewidth': 2})\n",
        "# Add R and R² text\n",
        "plt.annotate(f'r = {r_train_test:.3f}\\nr² = {r2_train_test:.3f}',\n",
        "             xy=(0.05, 0.90), xycoords='axes fraction',\n",
        "             bbox=dict(boxstyle=\"round,pad=0.3\", fc=\"white\", ec=\"gray\", alpha=0.8))\n",
        "plt.title('Training vs. Test Error')\n",
        "plt.xlabel('Training Error')\n",
        "plt.ylabel('Test Error')\n",
        "\n",
        "# Second plot: Training vs Holdout Error\n",
        "plt.subplot(1, 3, 2)\n",
        "# Calculate correlation coefficient (R) and p-value\n",
        "r_train_holdout, p_train_holdout = stats.pearsonr(bank_results_df['Training Error'], bank_results_df['Holdout Error'])\n",
        "r2_train_holdout = r_train_holdout**2\n",
        "# Add regression plot\n",
        "sns.regplot(data=bank_results_df, x='Training Error', y='Holdout Error',\n",
        "            scatter_kws={'color': custom_colors[1]},\n",
        "            line_kws={'color': custom_colors[1], 'linewidth': 2})\n",
        "# Add R and R² text\n",
        "plt.annotate(f'r = {r_train_holdout:.3f}\\nr² = {r2_train_holdout:.3f}',\n",
        "             xy=(0.05, 0.90), xycoords='axes fraction',\n",
        "             bbox=dict(boxstyle=\"round,pad=0.3\", fc=\"white\", ec=\"gray\", alpha=0.8))\n",
        "plt.title('Training vs. Holdout Error')\n",
        "plt.xlabel('Training Error')\n",
        "plt.ylabel('Holdout Error')\n",
        "\n",
        "# Third plot: Test vs Holdout Error\n",
        "plt.subplot(1, 3, 3)\n",
        "# Calculate correlation coefficient (R) and p-value\n",
        "r_test_holdout, p_test_holdout = stats.pearsonr(bank_results_df['Test Error'], bank_results_df['Holdout Error'])\n",
        "r2_test_holdout = r_test_holdout**2\n",
        "# Add regression plot\n",
        "sns.regplot(data=bank_results_df, x='Test Error', y='Holdout Error',\n",
        "            scatter_kws={'color': custom_colors[2]},\n",
        "            line_kws={'color': custom_colors[2], 'linewidth': 2})\n",
        "# Add R and R² text\n",
        "plt.annotate(f'r = {r_test_holdout:.3f}\\nr² = {r2_test_holdout:.3f}',\n",
        "             xy=(0.05, 0.90), xycoords='axes fraction',\n",
        "             bbox=dict(boxstyle=\"round,pad=0.3\", fc=\"white\", ec=\"gray\", alpha=0.8))\n",
        "plt.title('Test vs. Holdout Error')\n",
        "plt.xlabel('Test Error')\n",
        "plt.ylabel('Holdout Error')\n",
        "\n",
        "# Adjust layout to prevent overlap\n",
        "plt.tight_layout()\n",
        "\n",
        "# Show the plots\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 377
        },
        "id": "2p7-ixnrAhfi",
        "outputId": "01887482-a355-42e0-d67a-7c62da0d23c8"
      },
      "id": "2p7-ixnrAhfi",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1800x500 with 3 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Interpretation of Results (UCI Bank Marketing)\n",
        "\n",
        "Here we again see anti-correlation in both Training vs. Test Error and Training vs. Holdout Error plots, with similiar values of both $r$ and $r^2$. This is most likely to do with some hidden effects in $p_{\\rm train}(\\delta) = \\mu - \\alpha\\,\\delta$."
      ],
      "metadata": {
        "id": "brHVh2ie1JLN"
      },
      "id": "brHVh2ie1JLN"
    },
    {
      "cell_type": "markdown",
      "id": "WSMoPfCqnUpc",
      "metadata": {
        "id": "WSMoPfCqnUpc"
      },
      "source": [
        "# Repeated Trials with Synthetic Data\n",
        "\n",
        "#### We then wanted to control the conditions and see if we could assess model impacts more directly, below we created data with a linear boundary off of one feature and a more complex linear boundary with multiple features creating the boundary. We also randomly flip 30% of the targets to introduce noise. We then ran the same AdaBoost CV procedure as before."
      ]
    },
    {
      "cell_type": "markdown",
      "id": "a7xooNLAJZp9",
      "metadata": {
        "id": "a7xooNLAJZp9"
      },
      "source": [
        "## Analysis of Simple Synthetic Data\n",
        "\n",
        "#### Data was generated with 10 total features and 1000 instances, where one feature determined the target binary classification. We randomly selected 30% of target value bits to be flipped to introduce noise."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "id": "j6ZL38j-aP4D",
      "metadata": {
        "id": "j6ZL38j-aP4D"
      },
      "outputs": [],
      "source": [
        "def generate_linear_data(noise_level=0.3, random_state=None):\n",
        "    rng = np.random.RandomState(random_state)\n",
        "    X = rng.rand(1000, 10)  # 1000 samples, 10 features\n",
        "\n",
        "    # Linear relationship with first feature\n",
        "    y = (X[:, 0] > 0.5).astype(int)\n",
        "\n",
        "    # Add noise\n",
        "    if noise_level > 0:\n",
        "        flip_indices = rng.choice(1000, size=int(1000 * noise_level), replace=False)\n",
        "        y[flip_indices] = 1 - y[flip_indices]\n",
        "\n",
        "    return X, y\n",
        "\n",
        "# Define your base learner (decision stump is common with AdaBoost)\n",
        "base_learner = DecisionTreeClassifier(max_depth=1)\n",
        "\n",
        "n_runs = 100\n",
        "# Initialize result list\n",
        "results_linear = []\n",
        "\n",
        "X, y = generate_linear_data(noise_level=0.3, random_state=99)\n",
        "for seed in range(n_runs):\n",
        "        X_train_val, X_holdout, y_train_val, y_holdout = train_test_split(X, y, test_size=0.1, random_state=seed)\n",
        "        X_train, X_test, y_train, y_test = train_test_split(X_train_val, y_train_val, test_size=0.25, random_state=seed)\n",
        "\n",
        "        clf = AdaBoostClassifier(estimator=base_learner, n_estimators=50, random_state=seed)\n",
        "        clf.fit(X_train, y_train)\n",
        "\n",
        "        train_error = 1 - accuracy_score(y_train, clf.predict(X_train))\n",
        "        test_error = 1 - accuracy_score(y_test, clf.predict(X_test))\n",
        "        holdout_error = 1 - accuracy_score(y_holdout, clf.predict(X_holdout))\n",
        "\n",
        "        results_linear.append({\n",
        "            'seed': seed,\n",
        "            'train_error': train_error,\n",
        "            'test_error': test_error,\n",
        "            'holdout_error': holdout_error\n",
        "        })\n",
        "\n",
        "# Convert to DataFrames\n",
        "df_linear = pd.DataFrame(results_linear)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "id": "i2ezYunlhAof",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 373
        },
        "id": "i2ezYunlhAof",
        "outputId": "b03d4e87-ac22-4eec-c43d-1c977ba234e6"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1800x500 with 3 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "# Set up the seaborn aesthetics\n",
        "sns.set(style='whitegrid', context='notebook')\n",
        "\n",
        "plt.figure(figsize=(18, 5))\n",
        "\n",
        "# Define custom colors\n",
        "custom_colors = [\"#2ecc71\", \"#e74c3c\", \"#3498db\"]  # green, red, blue\n",
        "sns.set_palette(custom_colors)\n",
        "sns.set(style='whitegrid', context='notebook')\n",
        "\n",
        "\n",
        "# Define the error pairs to plot\n",
        "error_pairs = [\n",
        "    ('train_error', 'test_error'),\n",
        "    ('train_error', 'holdout_error'),\n",
        "    ('test_error', 'holdout_error')\n",
        "]\n",
        "# Loop through subplots\n",
        "for i, (x, y) in enumerate(error_pairs, start=1):\n",
        "    plt.subplot(1, 3, i)\n",
        "\n",
        "    # Calculate correlation and R²\n",
        "    r, _ = pearsonr(df_linear[x], df_linear[y])\n",
        "    r2 = r ** 2\n",
        "\n",
        "    # Regression plot\n",
        "    sns.regplot(\n",
        "        data=df_linear,\n",
        "        x=x, y=y,\n",
        "        scatter_kws={'color': custom_colors[i - 1], 'alpha': 0.6},\n",
        "        line_kws={'color': custom_colors[i - 1], 'linewidth': 2}\n",
        "    )\n",
        "\n",
        "    # Annotate with r and r²\n",
        "    plt.annotate(f'r = {r:.3f}\\nr² = {r2:.3f}',\n",
        "                 xy=(0.05, 0.90), xycoords='axes fraction',\n",
        "                 fontsize=12,\n",
        "                 bbox=dict(boxstyle=\"round,pad=0.3\", fc=\"white\", ec=\"gray\", alpha=0.8))\n",
        "\n",
        "    # Titles and labels\n",
        "    #plt.title(f'{x} vs. {y}')\n",
        "    plt.xlabel(x.replace('_', ' ').title())\n",
        "    plt.ylabel(y.replace('_', ' ').title())\n",
        "\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Interpretation of Results (Simple Synthetic)\n",
        "\n",
        "#### Again we see the strong anti-correlation between Test and Train error, in this simple model however, we don't see any notable correlation in the other plots, suggesting less over-fitting in this model."
      ],
      "metadata": {
        "id": "fj1SzizYOZ1Y"
      },
      "id": "fj1SzizYOZ1Y"
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Analysis of Complex Synthetic Data\n",
        "\n",
        "#### Here we generated data and analyzed it in a similar way, this time just varying the amount of influential features in determining the target variable label, to create a more complex linearly seperable boundary."
      ],
      "metadata": {
        "id": "MqMQ3ifbCRwr"
      },
      "id": "MqMQ3ifbCRwr"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "UbR-jVFSurwH",
      "metadata": {
        "collapsed": true,
        "id": "UbR-jVFSurwH"
      },
      "outputs": [],
      "source": [
        "# Synthetic data generator\n",
        "import numpy as np\n",
        "from sklearn.utils import shuffle\n",
        "\n",
        "def generate_linear_data(noise_level=0.3, random_state=None):\n",
        "    rng = np.random.RandomState(random_state)\n",
        "    X = rng.rand(1000, 10)  # Uniform [0, 1] features\n",
        "\n",
        "    # Linearly combine several features\n",
        "    weights = np.array([1.0,  1.0, .5])  # Example weights for features\n",
        "    linear_combo = X[:, :3] @ weights     # Dot product: shape (1000,)\n",
        "\n",
        "    # Decision boundary: label = 1 if linear combo > threshold\n",
        "    y = (linear_combo > 0.5).astype(int)\n",
        "\n",
        "    # Add label noise\n",
        "    if noise_level > 0:\n",
        "        flip_indices = rng.choice(len(y), size=int(len(y) * noise_level), replace=False)\n",
        "        y[flip_indices] = 1 - y[flip_indices]\n",
        "\n",
        "    return X, y\n",
        "def generate_linear_data_simp(noise_level=0.3, random_state=None):\n",
        "    rng = np.random.RandomState(random_state)\n",
        "    X = rng.rand(1000, 10)  # 1000 samples, 10 features\n",
        "\n",
        "    # Linear relationship with first feature\n",
        "    y = (X[:, 0] > 0.5).astype(int)\n",
        "\n",
        "    # Add noise\n",
        "    if noise_level > 0:\n",
        "        flip_indices = rng.choice(1000, size=int(1000 * noise_level), replace=False)\n",
        "        y[flip_indices] = 1 - y[flip_indices]\n",
        "\n",
        "    return X, y\n",
        "\n",
        "from sklearn.tree import DecisionTreeClassifier\n",
        "base_learner = DecisionTreeClassifier(max_depth=1)\n",
        "\n",
        "results2 = []\n",
        "# Generate data\n",
        "X, y = generate_linear_data(noise_level=.3, random_state=99)\n",
        "n_runs = 100\n",
        "\n",
        "for seed in range(n_runs):\n",
        "        X_train_val, X_holdout, y_train_val, y_holdout = train_test_split(X, y, test_size=0.1, random_state=seed)\n",
        "        X_train, X_test, y_train, y_test = train_test_split(X_train_val, y_train_val, test_size=0.25, random_state=seed)\n",
        "\n",
        "        clf = AdaBoostClassifier(estimator=base_learner, n_estimators=50, random_state=seed)\n",
        "        clf.fit(X_train, y_train)\n",
        "\n",
        "        train_error = 1 - accuracy_score(y_train, clf.predict(X_train))\n",
        "        test_error = 1 - accuracy_score(y_test, clf.predict(X_test))\n",
        "        holdout_error = 1 - accuracy_score(y_holdout, clf.predict(X_holdout))\n",
        "\n",
        "        results2.append({\n",
        "            'seed': seed,\n",
        "            'Training Error': train_error,\n",
        "            'Test Error': test_error,\n",
        "            'Holdout Error': holdout_error\n",
        "        })\n",
        "\n",
        "# Final DataFrame\n",
        "results2_df = pd.DataFrame(results2)\n"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Visualization of Synthetic Data with Multiple Signal Features"
      ],
      "metadata": {
        "id": "5OrVGacx-y1r"
      },
      "id": "5OrVGacx-y1r"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "0353bf06",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 373
        },
        "id": "0353bf06",
        "outputId": "a95c39e6-d40e-4090-e8da-6efe6e1043fd"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1800x500 with 3 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "# Set figure size for a row of 3 plots\n",
        "plt.figure(figsize=(18, 5))\n",
        "\n",
        "# Define custom colors\n",
        "custom_colors = [\"#2ecc71\",  # Green\n",
        "                 \"#e74c3c\",  # Red\n",
        "                 \"#3498db\",  # Blue\n",
        "                 \"#9b59b6\"]  # Purple\n",
        "sns.set_palette(custom_colors)\n",
        "\n",
        "# First plot: Training vs Test Error\n",
        "plt.subplot(1, 3, 1)\n",
        "# Calculate correlation coefficient (R) and p-value\n",
        "r_train_test, p_train_test = stats.pearsonr(results2_df['Training Error'], results2_df['Test Error'])\n",
        "r2_train_test = r_train_test**2\n",
        "# Add regression plot\n",
        "sns.regplot(data=results2_df, x='Training Error', y='Test Error',\n",
        "            scatter_kws={'color': custom_colors[0]},\n",
        "            line_kws={'color': custom_colors[0], 'linewidth': 2})\n",
        "# Add R and R² text\n",
        "plt.annotate(f'r = {r_train_test:.3f}\\nr² = {r2_train_test:.3f}',\n",
        "             xy=(0.05, 0.90), xycoords='axes fraction',\n",
        "             bbox=dict(boxstyle=\"round,pad=0.3\", fc=\"white\", ec=\"gray\", alpha=0.8))\n",
        "plt.title('Training vs. Test Error')\n",
        "plt.xlabel('Training Error')\n",
        "plt.ylabel('Test Error')\n",
        "\n",
        "# Second plot: Training vs Holdout Error\n",
        "plt.subplot(1, 3, 2)\n",
        "# Calculate correlation coefficient (R) and p-value\n",
        "r_train_holdout, p_train_holdout = stats.pearsonr(results2_df['Training Error'], results2_df['Holdout Error'])\n",
        "r2_train_holdout = r_train_holdout**2\n",
        "# Add regression plot\n",
        "sns.regplot(data=results2_df, x='Training Error', y='Holdout Error',\n",
        "            scatter_kws={'color': custom_colors[1]},\n",
        "            line_kws={'color': custom_colors[1], 'linewidth': 2})\n",
        "# Add R and R² text\n",
        "plt.annotate(f'r = {r_train_holdout:.3f}\\nr² = {r2_train_holdout:.3f}',\n",
        "             xy=(0.05, 0.90), xycoords='axes fraction',\n",
        "             bbox=dict(boxstyle=\"round,pad=0.3\", fc=\"white\", ec=\"gray\", alpha=0.8))\n",
        "plt.title('Training vs. Holdout Error')\n",
        "plt.xlabel('Training Error')\n",
        "plt.ylabel('Holdout Error')\n",
        "\n",
        "# Third plot: Test vs Holdout Error\n",
        "plt.subplot(1, 3, 3)\n",
        "# Calculate correlation coefficient (R) and p-value\n",
        "r_test_holdout, p_test_holdout = stats.pearsonr(results2_df['Test Error'], results2_df['Holdout Error'])\n",
        "r2_test_holdout = r_test_holdout**2\n",
        "# Add regression plot\n",
        "sns.regplot(data=results2_df, x='Test Error', y='Holdout Error',\n",
        "            scatter_kws={'color': custom_colors[2]},\n",
        "            line_kws={'color': custom_colors[2], 'linewidth': 2})\n",
        "# Add R and R² text\n",
        "plt.annotate(f'r = {r_test_holdout:.3f}\\nr² = {r2_test_holdout:.3f}',\n",
        "             xy=(0.05, 0.90), xycoords='axes fraction',\n",
        "             bbox=dict(boxstyle=\"round,pad=0.3\", fc=\"white\", ec=\"gray\", alpha=0.8))\n",
        "plt.title('Test vs. Holdout Error')\n",
        "plt.xlabel('Test Error')\n",
        "plt.ylabel('Holdout Error')\n",
        "\n",
        "# Adjust layout to prevent overlap\n",
        "plt.tight_layout()\n",
        "\n",
        "# Show the plots\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Interpretation of Results (Synthetic Data with Complex Linear Boundary)\n",
        "\n",
        "#### We see almost an exact prediction of our model results in the synthetic data: strong test:train anti-correlation, weaker holdout:train anti-correlation and basically no correlation in holdout:test."
      ],
      "metadata": {
        "id": "iz0ink0G-7p0"
      },
      "id": "iz0ink0G-7p0"
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **Appendix**\n",
        "## Future Directions to Consider\n",
        "#### Multi-class classification\n",
        "\n",
        "\n",
        "*   Running AdaBoost on a multiclass classification problem using SAMME.R, a real variant of Stagewise Additive Modeling using a Multi-class Exponential loss function that uses class probabilities from the base estimator. This procedure allows AdaBoost to run on non-binary classification tasks.\n",
        "\n",
        "\n",
        "*  We are computing empirical classification error, i.e., 0-1 loss. So there is no weighting done on the mislabeling.\n",
        "\n",
        "* We suspect that this diffuses anti-correlation, but must examine these effects further.\n",
        "\n"
      ],
      "metadata": {
        "id": "4SZBd9n5A0Nd"
      },
      "id": "4SZBd9n5A0Nd"
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Anaylsis of UCI Wine Quality Data Set\n",
        "\n",
        "#### Data of Portugal wines predicting their quality score. Processed slightly differently as this is now a multiclass classification problem. We are no longer using decision stumps, but trees of max length 3. We only consider red wines.\n",
        "\n",
        "## Relevant Features\n",
        "\n",
        "#### - Multiclass: (8) Possible target values\n",
        "#### - Medium Data set ~1.5k instances\n",
        "#### - 12 Features"
      ],
      "metadata": {
        "id": "kOwnCKgO3zTQ"
      },
      "id": "kOwnCKgO3zTQ"
    },
    {
      "cell_type": "code",
      "source": [
        "# 1. Load Wine Quality dataset (multiclass: target = wine quality score)\n",
        "def load_wine_data():\n",
        "    url = \"https://archive.ics.uci.edu/ml/machine-learning-databases/wine-quality/winequality-red.csv\"\n",
        "    response = requests.get(url)\n",
        "    data = pd.read_csv(StringIO(response.text), sep=';')\n",
        "\n",
        "    return data\n",
        "\n",
        "# 2. Preprocess the data\n",
        "def preprocess_wine_data(data):\n",
        "    X = data.drop('quality', axis=1)\n",
        "    y = data['quality']  # Multiclass target (scores like 3, 4, ..., 8)\n",
        "\n",
        "    numeric_features = X.columns.tolist()\n",
        "    numeric_transformer = StandardScaler()\n",
        "\n",
        "    preprocessor = ColumnTransformer(\n",
        "        transformers=[\n",
        "            ('num', numeric_transformer, numeric_features)\n",
        "        ])\n",
        "\n",
        "    return X, y, preprocessor\n",
        "\n",
        "# 3. Run the AdaBoost experiment\n",
        "def run_adaboost_experiment(X, y, preprocessor, n_runs=100):\n",
        "    base_learner = DecisionTreeClassifier(max_depth=3)\n",
        "    results = []\n",
        "\n",
        "    for seed in range(n_runs):\n",
        "        X_train_val, X_holdout, y_train_val, y_holdout = train_test_split(\n",
        "            X, y, test_size=0.1, random_state=seed, stratify=y)\n",
        "\n",
        "        X_train, X_test, y_train, y_test = train_test_split(\n",
        "            X_train_val, y_train_val, test_size=0.25, random_state=seed, stratify=y_train_val)\n",
        "\n",
        "        pipeline = Pipeline([\n",
        "            ('preprocessor', preprocessor),\n",
        "            ('classifier', AdaBoostClassifier(\n",
        "                estimator=base_learner,\n",
        "                n_estimators=50,\n",
        "                random_state=seed))\n",
        "        ])\n",
        "\n",
        "        pipeline.fit(X_train, y_train)\n",
        "\n",
        "        train_error = 1 - accuracy_score(y_train, pipeline.predict(X_train))\n",
        "        test_error = 1 - accuracy_score(y_test, pipeline.predict(X_test))\n",
        "        holdout_error = 1 - accuracy_score(y_holdout, pipeline.predict(X_holdout))\n",
        "\n",
        "        results.append({\n",
        "            'seed': seed,\n",
        "            'Training Error': train_error,\n",
        "            'Test Error': test_error,\n",
        "            'Holdout Error': holdout_error\n",
        "        })\n",
        "\n",
        "    return pd.DataFrame(results)\n",
        "\n",
        "# Run everything\n",
        "if __name__ == \"__main__\":\n",
        "    wine_data = load_wine_data()\n",
        "    print(f\"Dataset shape: {wine_data.shape}\")\n",
        "\n",
        "    X, y, preprocessor = preprocess_wine_data(wine_data)\n",
        "\n",
        "    wine_results = run_adaboost_experiment(X, y, preprocessor, n_runs=100)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "znujd2t8JVey",
        "outputId": "12d171f2-f9e9-408a-ab9b-d2df19f7e3e0"
      },
      "id": "znujd2t8JVey",
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Dataset shape: (1599, 12)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Visulation of Results (UCI Wine Quality)"
      ],
      "metadata": {
        "id": "G-SsQgna6iSw"
      },
      "id": "G-SsQgna6iSw"
    },
    {
      "cell_type": "code",
      "source": [
        "# Step 8: Set figure size for a row of 3 plots\n",
        "plt.figure(figsize=(18, 5))\n",
        "\n",
        "# Define custom colors\n",
        "custom_colors = [\"#2ecc71\",  # Green\n",
        "                 \"#e74c3c\",  # Red\n",
        "                 \"#3498db\",  # Blue\n",
        "                 \"#9b59b6\"]  # Purple\n",
        "sns.set_palette(custom_colors)\n",
        "\n",
        "# First plot: Training vs Test Error\n",
        "plt.subplot(1, 3, 1)\n",
        "# Calculate correlation coefficient (R) and p-value\n",
        "r_train_test, p_train_test = stats.pearsonr(wine_results['Training Error'], wine_results['Test Error'])\n",
        "r2_train_test = r_train_test**2\n",
        "# Add regression plot\n",
        "sns.regplot(data=wine_results, x='Training Error', y='Test Error',\n",
        "            scatter_kws={'color': custom_colors[0]},\n",
        "            line_kws={'color': custom_colors[0], 'linewidth': 2})\n",
        "# Add R and R² text\n",
        "plt.annotate(f'r = {r_train_test:.3f}\\nr² = {r2_train_test:.3f}',\n",
        "             xy=(0.05, 0.90), xycoords='axes fraction',\n",
        "             bbox=dict(boxstyle=\"round,pad=0.3\", fc=\"white\", ec=\"gray\", alpha=0.8))\n",
        "plt.title('Training vs. Test Error')\n",
        "plt.xlabel('Training Error')\n",
        "plt.ylabel('Test Error')\n",
        "\n",
        "# Second plot: Training vs Holdout Error\n",
        "plt.subplot(1, 3, 2)\n",
        "# Calculate correlation coefficient (R) and p-value\n",
        "r_train_holdout, p_train_holdout = stats.pearsonr(wine_results['Training Error'], wine_results['Holdout Error'])\n",
        "r2_train_holdout = r_train_holdout**2\n",
        "# Add regression plot\n",
        "sns.regplot(data=wine_results, x='Training Error', y='Holdout Error',\n",
        "            scatter_kws={'color': custom_colors[1]},\n",
        "            line_kws={'color': custom_colors[1], 'linewidth': 2})\n",
        "# Add R and R² text\n",
        "plt.annotate(f'r = {r_train_holdout:.3f}\\nr² = {r2_train_holdout:.3f}',\n",
        "             xy=(0.05, 0.90), xycoords='axes fraction',\n",
        "             bbox=dict(boxstyle=\"round,pad=0.3\", fc=\"white\", ec=\"gray\", alpha=0.8))\n",
        "plt.title('Training vs. Holdout Error')\n",
        "plt.xlabel('Training Error')\n",
        "plt.ylabel('Holdout Error')\n",
        "\n",
        "# Third plot: Test vs Holdout Error\n",
        "plt.subplot(1, 3, 3)\n",
        "# Calculate correlation coefficient (R) and p-value\n",
        "r_test_holdout, p_test_holdout = stats.pearsonr(wine_results['Test Error'], wine_results['Holdout Error'])\n",
        "r2_test_holdout = r_test_holdout**2\n",
        "# Add regression plot\n",
        "sns.regplot(data=wine_results, x='Test Error', y='Holdout Error',\n",
        "            scatter_kws={'color': custom_colors[2]},\n",
        "            line_kws={'color': custom_colors[2], 'linewidth': 2})\n",
        "# Add R and R² text\n",
        "plt.annotate(f'r = {r_test_holdout:.3f}\\nr² = {r2_test_holdout:.3f}',\n",
        "             xy=(0.05, 0.90), xycoords='axes fraction',\n",
        "             bbox=dict(boxstyle=\"round,pad=0.3\", fc=\"white\", ec=\"gray\", alpha=0.8))\n",
        "plt.title('Test vs. Holdout Error')\n",
        "plt.xlabel('Test Error')\n",
        "plt.ylabel('Holdout Error')\n",
        "\n",
        "# Adjust layout to prevent overlap\n",
        "plt.tight_layout()\n",
        "\n",
        "# Show the plots\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 376
        },
        "id": "DE59nvNzJde8",
        "outputId": "d24ea01f-1088-491f-91d6-3557aa361041"
      },
      "id": "DE59nvNzJde8",
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1800x500 with 3 Axes>"
            ],
            "image/png": 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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Interpretation of Results (UCI Wine Quality)\n",
        "\n",
        "#### We have lost the anti-correlation and see a very vague correlation between test and train. This is expected, in binary classification, each example is either right or wrong based on one threshold. In multiclass, there are multiple possible ways to be wrong; diffusing the impact of overfitting. Thus, the variance of error rates per fold can be lower creating a less pronounced covariance structure."
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