HappinessSurvey.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "bdfb717d-3803-445e-be06-c12df2138158",
   "metadata": {},
   "source": [
    "Technical Report: Building and Tuning Classification Models for Happiness Prediction\n",
    "\n",
    "Introduction\n",
    "\n",
    "In this technical report, we will walk through the process of building and tuning classification models for the task of predicting happiness levels based on a dataset called 'ACME-HappinessSurvey2020.csv'. We will use Python's Scikit-Learn library for machine learning and several classification algorithms to achieve this. The primary goal is to select the best-performing model for predicting happiness levels.\n",
    "\n",
    "Libraries Used\n",
    "Pandas: Used for data loading and manipulation.\n",
    "Scikit-Learn: Used for machine learning tasks such as model selection, preprocessing, and evaluation.\n",
    "XGBoost: An optimized gradient boosting library.\n",
    "Warning: Used to suppress warning messages."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c700fea8-0e03-4bbd-b9c9-ec0168ea7761",
   "metadata": {},
   "source": [
    "Data Loading and Preprocessing\n",
    "\n",
    "The initial steps involve loading the dataset and preparing the data for machine learning."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "04691a28-508d-42a5-9c22-bbd3085a39b8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data Overview:\n",
      "   Y  X1  X2  X3  X4  X5  X6\n",
      "0  0   3   3   3   4   2   4\n",
      "1  0   3   2   3   5   4   3\n",
      "2  1   5   3   3   3   3   5\n",
      "3  0   5   4   3   3   3   5\n",
      "4  0   5   4   3   3   3   5\n",
      "\n",
      "Data Summary:\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 126 entries, 0 to 125\n",
      "Data columns (total 7 columns):\n",
      " #   Column  Non-Null Count  Dtype\n",
      "---  ------  --------------  -----\n",
      " 0   Y       126 non-null    int64\n",
      " 1   X1      126 non-null    int64\n",
      " 2   X2      126 non-null    int64\n",
      " 3   X3      126 non-null    int64\n",
      " 4   X4      126 non-null    int64\n",
      " 5   X5      126 non-null    int64\n",
      " 6   X6      126 non-null    int64\n",
      "dtypes: int64(7)\n",
      "memory usage: 7.0 KB\n",
      "None\n",
      "\n",
      "Statistics for Numerical Features:\n",
      "                Y          X1          X2          X3          X4          X5  \\\n",
      "count  126.000000  126.000000  126.000000  126.000000  126.000000  126.000000   \n",
      "mean     0.547619    4.333333    2.531746    3.309524    3.746032    3.650794   \n",
      "std      0.499714    0.800000    1.114892    1.023440    0.875776    1.147641   \n",
      "min      0.000000    1.000000    1.000000    1.000000    1.000000    1.000000   \n",
      "25%      0.000000    4.000000    2.000000    3.000000    3.000000    3.000000   \n",
      "50%      1.000000    5.000000    3.000000    3.000000    4.000000    4.000000   \n",
      "75%      1.000000    5.000000    3.000000    4.000000    4.000000    4.000000   \n",
      "max      1.000000    5.000000    5.000000    5.000000    5.000000    5.000000   \n",
      "\n",
      "               X6  \n",
      "count  126.000000  \n",
      "mean     4.253968  \n",
      "std      0.809311  \n",
      "min      1.000000  \n",
      "25%      4.000000  \n",
      "50%      4.000000  \n",
      "75%      5.000000  \n",
      "max      5.000000  \n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "# Load the dataset\n",
    "df = pd.read_csv('ACME-HappinessSurvey2020.csv')\n",
    "\n",
    "# Data Overview\n",
    "print(\"Data Overview:\")\n",
    "print(df.head())\n",
    "\n",
    "# Data Summary\n",
    "print(\"\\nData Summary:\")\n",
    "print(df.info())\n",
    "print(\"\\nStatistics for Numerical Features:\")\n",
    "print(df.describe())\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "61eaf1f2-dca9-4b65-b9a8-603720fcd1ff",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Unique Values in Categorical Features:\n",
      "Feature: Y\n",
      "Y\n",
      "1    69\n",
      "0    57\n",
      "Name: count, dtype: int64\n",
      "Feature: X1\n",
      "X1\n",
      "5    65\n",
      "4    40\n",
      "3    20\n",
      "1     1\n",
      "Name: count, dtype: int64\n",
      "Feature: X2\n",
      "X2\n",
      "3    42\n",
      "2    34\n",
      "1    27\n",
      "4    17\n",
      "5     6\n",
      "Name: count, dtype: int64\n",
      "Feature: X3\n",
      "X3\n",
      "3    55\n",
      "4    33\n",
      "5    17\n",
      "2    14\n",
      "1     7\n",
      "Name: count, dtype: int64\n",
      "Feature: X4\n",
      "X4\n",
      "4    53\n",
      "3    41\n",
      "5    25\n",
      "2     5\n",
      "1     2\n",
      "Name: count, dtype: int64\n",
      "Feature: X5\n",
      "X5\n",
      "4    50\n",
      "5    31\n",
      "3    22\n",
      "2    16\n",
      "1     7\n",
      "Name: count, dtype: int64\n",
      "Feature: X6\n",
      "X6\n",
      "5    57\n",
      "4    47\n",
      "3    20\n",
      "2     1\n",
      "1     1\n",
      "Name: count, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print(\"\\nUnique Values in Categorical Features:\")\n",
    "categorical_features = df.columns\n",
    "for feature in categorical_features:\n",
    "    print(f\"Feature: {feature}\")\n",
    "    print(df[feature].value_counts())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "a2de69fb-7b06-44e0-9291-897f4adf207c",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1200x600 with 7 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Data Visualization\n",
    "plt.figure(figsize=(12, 6))\n",
    "\n",
    "# Histograms for Numerical Features\n",
    "for feature in df.select_dtypes(include=['int64', 'float64']).columns:\n",
    "    plt.subplot(2, 4, df.columns.get_loc(feature)+1)\n",
    "    sns.histplot(df[feature], bins=20, kde=True)\n",
    "    plt.title(f'Distribution of {feature}')\n",
    "    plt.xlabel(feature)\n",
    "    plt.ylabel('Frequency')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "2562cae7-9257-4d7b-acf0-dd8e84f87d54",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Bar plots for Categorical Features\n",
    "for feature in categorical_features:\n",
    "    plt.figure(figsize=(10, 4))\n",
    "    sns.countplot(data=df, x=feature, order=df[feature].value_counts().index)\n",
    "    plt.title(f'Count of {feature}')\n",
    "    plt.xlabel(feature)\n",
    "    plt.ylabel('Count')\n",
    "    plt.xticks(rotation=45)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "ab5ddc2d-11bf-475c-84df-7ea6eb173d72",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Correlation Matrix')"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Correlation Matrix for Numerical Features\n",
    "correlation_matrix = df.corr()\n",
    "plt.figure(figsize=(8, 6))\n",
    "sns.heatmap(correlation_matrix, annot=True, cmap='coolwarm', fmt=\".2f\")\n",
    "plt.title('Correlation Matrix')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "5320f88c-d6eb-4731-9286-8cbcea276bc5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.02, 'Pairplot for Relationships')"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1558.88x1500 with 42 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Pairplot for Relationships\n",
    "sns.pairplot(df, hue='Y', diag_kind='kde')\n",
    "plt.suptitle('Pairplot for Relationships', y=1.02)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "9c7e90b4-cbdf-412c-b6b8-04477ca26249",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Target Variable Analysis\n",
    "plt.figure(figsize=(6, 4))\n",
    "sns.countplot(data=df, x='Y')\n",
    "plt.title('Distribution of Target Variable \"Y\"')\n",
    "plt.xlabel('Y')\n",
    "plt.ylabel('Count')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "ac0567d0-22c8-49a2-9e51-3527757737c1",
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "import pandas as pd\n",
    "from sklearn.model_selection import train_test_split, GridSearchCV, StratifiedKFold\n",
    "from sklearn.metrics import accuracy_score\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from xgboost import XGBClassifier\n",
    "from sklearn.ensemble import RandomForestClassifier, GradientBoostingClassifier\n",
    "from sklearn.svm import SVC\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Ignore warnings\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "\n",
    "\n",
    "# Loading data from CSV to df\n",
    "df = pd.read_csv('ACME-HappinessSurvey2020.csv')  # If your data is in a CSV file\n",
    "\n",
    "# Defining features and target\n",
    "X = df.drop('Y', axis=1)\n",
    "y = df['Y']\n",
    "# Preprocess the data\n",
    "scaler = StandardScaler()\n",
    "X_scaled = scaler.fit_transform(X)\n",
    "\n",
    "\n",
    "# Create a stratified split to maintain the class distribution\n",
    "stratified_kfold = StratifiedKFold(n_splits=5, shuffle=True, random_state=42)\n",
    "# split the data to train the final model\n",
    "X_train, X_test, y_train, y_test = train_test_split(X_scaled, y, test_size=0.2, random_state=42, stratify=y)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "4e3190e8-7158-45d4-af2e-2c3dc42dbb5d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 6 candidates, totalling 30 fits\n",
      "Accuracy on the test set for Logistic Regression: 0.6153846153846154\n"
     ]
    }
   ],
   "source": [
    "# Logistic Regression\n",
    "lr_model = LogisticRegression(random_state=42)\n",
    "\n",
    "param_grid_lr = {\n",
    "    'penalty': ['l1', 'l2'],\n",
    "    'C': [0.1, 1, 10],\n",
    "}\n",
    "\n",
    "# GridSearchCV for parameter tuning\n",
    "grid_search_lr = GridSearchCV(\n",
    "    estimator=lr_model,\n",
    "    param_grid=param_grid_lr,\n",
    "    cv=stratified_kfold,\n",
    "    verbose=1,\n",
    "    scoring='accuracy',\n",
    "    n_jobs=-1\n",
    ")\n",
    "\n",
    "grid_search_lr.fit(X_scaled, y)\n",
    "\n",
    "# Training the final Logistic Regression model on the full training set using the best parameters\n",
    "best_lr_model = grid_search_lr.best_estimator_\n",
    "best_lr_model.fit(X_train, y_train)\n",
    "\n",
    "# Predicting on the test set with the best Logistic Regression model\n",
    "y_pred_lr = best_lr_model.predict(X_test)\n",
    "\n",
    "# Calculating the accuracy on the test set for Logistic Regression\n",
    "test_accuracy_lr = accuracy_score(y_test, y_pred_lr)\n",
    "print(f'Accuracy on the test set for Logistic Regression: {test_accuracy_lr}')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "e15a3d55-c77c-479e-a623-5f5a2477738e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 24 candidates, totalling 120 fits\n",
      "Accuracy on the test set for SVC: 0.6538461538461539\n"
     ]
    }
   ],
   "source": [
    "# Support Vector Classifier (SVC)\n",
    "svc_model = SVC(random_state=42)\n",
    "\n",
    "param_grid_svc = {\n",
    "    'C': [0.1, 1, 10],\n",
    "    'kernel': ['linear', 'rbf'],\n",
    "    'gamma': ['scale', 'auto'] + [0.1, 0.2],\n",
    "}\n",
    "\n",
    "# GridSearchCV for parameter tuning\n",
    "grid_search_svc = GridSearchCV(\n",
    "    estimator=svc_model,\n",
    "    param_grid=param_grid_svc,\n",
    "    cv=stratified_kfold,\n",
    "    verbose=1,\n",
    "    scoring='accuracy',\n",
    "    n_jobs=-1\n",
    ")\n",
    "\n",
    "grid_search_svc.fit(X_scaled, y)\n",
    "\n",
    "# Training the final SVC model on the full training set using the best parameters\n",
    "best_svc_model = grid_search_svc.best_estimator_\n",
    "best_svc_model.fit(X_train, y_train)\n",
    "\n",
    "# Predicting on the test set with the best SVC model\n",
    "y_pred_svc = best_svc_model.predict(X_test)\n",
    "\n",
    "# Calculating the accuracy on the test set for SVC\n",
    "test_accuracy_svc = accuracy_score(y_test, y_pred_svc)\n",
    "print(f'Accuracy on the test set for SVC: {test_accuracy_svc}')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "a7db491e-bccb-423f-a3d1-917f3da9965f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 216 candidates, totalling 1080 fits\n",
      "Accuracy on the test set for Gradient Boosting: 0.46153846153846156\n"
     ]
    }
   ],
   "source": [
    "# Gradient Boosting Classifier\n",
    "gb_model = GradientBoostingClassifier(random_state=42)\n",
    "\n",
    "param_grid_gb = {\n",
    "    'n_estimators': [50, 100, 150],\n",
    "    'learning_rate': [0.05, 0.1],\n",
    "    'max_depth': [3, 4],\n",
    "    'subsample': [0.7, 0.8],\n",
    "    'min_samples_split': [2, 5, 10],\n",
    "    'min_samples_leaf': [1, 2, 4],\n",
    "}\n",
    "\n",
    "# GridSearchCV for parameter tuning\n",
    "grid_search_gb = GridSearchCV(\n",
    "    estimator=gb_model,\n",
    "    param_grid=param_grid_gb,\n",
    "    cv=stratified_kfold,\n",
    "    verbose=1,\n",
    "    scoring='accuracy',\n",
    "    n_jobs=-1\n",
    ")\n",
    "\n",
    "grid_search_gb.fit(X_scaled, y)\n",
    "\n",
    "# Training the final Gradient Boosting model on the full training set using the best parameters\n",
    "best_gb_model = grid_search_gb.best_estimator_\n",
    "best_gb_model.fit(X_train, y_train)\n",
    "\n",
    "# Predicting on the test set with the best Gradient Boosting model\n",
    "y_pred_gb = best_gb_model.predict(X_test)\n",
    "\n",
    "# Calculating the accuracy on the test set for Gradient Boosting\n",
    "test_accuracy_gb = accuracy_score(y_test, y_pred_gb)\n",
    "print(f'Accuracy on the test set for Gradient Boosting: {test_accuracy_gb}')\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "e6075a6f-294f-471b-b80e-20f2fa3055c8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 162 candidates, totalling 810 fits\n",
      "Accuracy on the test set for Random Forest: 0.7307692307692307\n"
     ]
    }
   ],
   "source": [
    "# Random Forest Classifier\n",
    "rf_model = RandomForestClassifier(random_state=42)\n",
    "\n",
    "param_grid_rf = {\n",
    "    'n_estimators': [50, 100, 150],\n",
    "    'max_depth': [3, 4, None],\n",
    "    'min_samples_split': [2, 5, 10],\n",
    "    'min_samples_leaf': [1, 2, 4],\n",
    "    'max_features': ['auto', 'sqrt'],\n",
    "}\n",
    "\n",
    "# GridSearchCV for parameter tuning\n",
    "grid_search_rf = GridSearchCV(\n",
    "    estimator=rf_model,\n",
    "    param_grid=param_grid_rf,\n",
    "    cv=stratified_kfold,\n",
    "    verbose=1,\n",
    "    scoring='accuracy',\n",
    "    n_jobs=-1\n",
    ")\n",
    "\n",
    "grid_search_rf.fit(X_scaled, y)\n",
    "\n",
    "# Training the final Random Forest model on the full training set using the best parameters\n",
    "best_rf_model = grid_search_rf.best_estimator_\n",
    "best_rf_model.fit(X_train, y_train)\n",
    "\n",
    "# Predicting on the test set with the best Random Forest model\n",
    "y_pred_rf = best_rf_model.predict(X_test)\n",
    "\n",
    "# Calculating the accuracy on the test set for Random Forest\n",
    "test_accuracy_rf = accuracy_score(y_test, y_pred_rf)\n",
    "print(f'Accuracy on the test set for Random Forest: {test_accuracy_rf}')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "b1d21ac2-ff6a-405d-aa39-4e940de40345",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 1152 candidates, totalling 5760 fits\n",
      "Best parameters found:  {'colsample_bytree': 0.7, 'gamma': 0.2, 'learning_rate': 0.05, 'max_depth': 3, 'n_estimators': 100, 'reg_alpha': 0.3, 'reg_lambda': 3, 'subsample': 0.8}\n",
      "Best cross-validated accuracy found:  0.6196923076923078\n",
      "Accuracy on the test set: 0.7692307692307693\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "from sklearn.model_selection import train_test_split, GridSearchCV, StratifiedKFold\n",
    "from sklearn.metrics import accuracy_score\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from xgboost import XGBClassifier\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "\n",
    "\n",
    "# Initialize the XGBClassifier\n",
    "xgb_model = XGBClassifier(use_label_encoder=False, eval_metric='logloss')\n",
    "\n",
    "# Create a parameter grid with narrowed focus and increased regularization\n",
    "param_grid = {\n",
    "    'n_estimators': [50, 100, 150],\n",
    "    'learning_rate': [0.05, 0.1],\n",
    "    'max_depth': [3, 4],\n",
    "    'colsample_bytree': [0.7, 0.8],\n",
    "    'subsample': [0.7, 0.8],\n",
    "    'gamma': [0.1, 0.2],\n",
    "    'reg_lambda': [1, 1.5, 2, 3],  # Increased regularization\n",
    "    'reg_alpha': [0.1, 0.2, 0.3]\n",
    "}\n",
    "\n",
    "# Setup the GridSearchCV object with stratified K-Fold\n",
    "grid_search = GridSearchCV(\n",
    "    estimator=xgb_model,\n",
    "    param_grid=param_grid,\n",
    "    cv=stratified_kfold,\n",
    "    verbose=1,\n",
    "    scoring='accuracy',\n",
    "    n_jobs=-1\n",
    ")\n",
    "\n",
    "# Performing the grid search\n",
    "grid_search.fit(X_scaled, y)\n",
    "\n",
    "# Best parameters and best score\n",
    "print(\"Best parameters found: \", grid_search.best_params_)\n",
    "print(\"Best cross-validated accuracy found: \", grid_search.best_score_)\n",
    "\n",
    "\n",
    "# Training the final model on the full training set using the best parameters\n",
    "best_model = grid_search.best_estimator_\n",
    "best_model.fit(X_train, y_train)\n",
    "\n",
    "# Predicting on the test set with the best parameters\n",
    "y_pred = best_model.predict(X_test)\n",
    "\n",
    "# Calculate the accuracy on the test set\n",
    "test_accuracy = accuracy_score(y_test, y_pred)\n",
    "print(f'Accuracy on the test set: {test_accuracy}')\n",
    "\n",
    "# Plot the accuracies\n",
    "plt.figure(figsize=(8, 6))\n",
    "plt.bar(['Test Accuracy'], [test_accuracy])\n",
    "plt.ylim(0, 1)\n",
    "plt.ylabel('Accuracy')\n",
    "plt.title('Test Set Accuracy')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "f37488a3-237b-470f-854a-069f1fec866a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 1152 candidates, totalling 5760 fits\n",
      "Best parameters found for XGBClassifier:  {'colsample_bytree': 0.7, 'gamma': 0.2, 'learning_rate': 0.05, 'max_depth': 3, 'n_estimators': 100, 'reg_alpha': 0.3, 'reg_lambda': 3, 'subsample': 0.8}\n",
      "Best cross-validated accuracy found for XGBClassifier:  0.6196923076923078\n",
      "Accuracy on the test set for XGBClassifier: 0.7692307692307693\n",
      "Fitting 5 folds for each of 162 candidates, totalling 810 fits\n",
      "Best parameters found for RandomForestClassifier:  {'max_depth': 4, 'max_features': 'sqrt', 'min_samples_leaf': 2, 'min_samples_split': 2, 'n_estimators': 50}\n",
      "Best cross-validated accuracy found for RandomForestClassifier:  0.689846153846154\n",
      "Accuracy on the test set for RandomForestClassifier: 0.7307692307692307\n",
      "Fitting 5 folds for each of 216 candidates, totalling 1080 fits\n",
      "Best parameters found for GradientBoostingClassifier:  {'learning_rate': 0.1, 'max_depth': 3, 'min_samples_leaf': 1, 'min_samples_split': 5, 'n_estimators': 100, 'subsample': 0.7}\n",
      "Best cross-validated accuracy found for GradientBoostingClassifier:  0.6587692307692309\n",
      "Accuracy on the test set for GradientBoostingClassifier: 0.46153846153846156\n",
      "Fitting 5 folds for each of 24 candidates, totalling 120 fits\n",
      "Best parameters found for SVC:  {'C': 10, 'gamma': 'scale', 'kernel': 'linear'}\n",
      "Best cross-validated accuracy found for SVC:  0.6190769230769232\n",
      "Accuracy on the test set for SVC: 0.6538461538461539\n",
      "Fitting 5 folds for each of 6 candidates, totalling 30 fits\n",
      "Best parameters found for LogisticRegression:  {'C': 10, 'penalty': 'l2'}\n",
      "Best cross-validated accuracy found for LogisticRegression:  0.5630769230769231\n",
      "Accuracy on the test set for LogisticRegression: 0.6153846153846154\n",
      "Fitting 5 folds for each of 6 candidates, totalling 30 fits\n",
      "Best parameters found for KNeighborsClassifier:  {'n_neighbors': 7, 'weights': 'uniform'}\n",
      "Best cross-validated accuracy found for KNeighborsClassifier:  0.6027692307692308\n",
      "Accuracy on the test set for KNeighborsClassifier: 0.5384615384615384\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import warnings\n",
    "import pandas as pd\n",
    "from sklearn.model_selection import train_test_split, GridSearchCV, StratifiedKFold\n",
    "from sklearn.metrics import accuracy_score\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from xgboost import XGBClassifier\n",
    "from sklearn.ensemble import RandomForestClassifier, GradientBoostingClassifier\n",
    "from sklearn.svm import SVC\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Ignore warnings\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "\n",
    "\n",
    "# Loading data from CSV to df\n",
    "df = pd.read_csv('ACME-HappinessSurvey2020.csv')  # If your data is in a CSV file\n",
    "\n",
    "# Defining features and target\n",
    "X = df.drop('Y', axis=1)\n",
    "y = df['Y']\n",
    "# Preprocess the data\n",
    "scaler = StandardScaler()\n",
    "X_scaled = scaler.fit_transform(X)\n",
    "# spliting the data to train the final model\n",
    "X_train, X_test, y_train, y_test = train_test_split(X_scaled, y, test_size=0.2, random_state=42, stratify=y)\n",
    "\n",
    "\n",
    "# Create a stratified split to maintain the class distribution\n",
    "stratified_kfold = StratifiedKFold(n_splits=5, shuffle=True, random_state=42)\n",
    "\n",
    "# Initialize the models\n",
    "models = [\n",
    "    XGBClassifier(use_label_encoder=False, eval_metric='logloss'),\n",
    "    RandomForestClassifier(random_state=42),\n",
    "    GradientBoostingClassifier(random_state=42),\n",
    "    SVC(random_state=42),\n",
    "    LogisticRegression(random_state=42),\n",
    "    KNeighborsClassifier()\n",
    "]\n",
    "\n",
    "# Create a parameter grid for each model\n",
    "param_grids = [\n",
    "    {\n",
    "        'n_estimators': [50, 100, 150],\n",
    "        'learning_rate': [0.05, 0.1],\n",
    "        'max_depth': [3, 4],\n",
    "        'colsample_bytree': [0.7, 0.8],\n",
    "        'subsample': [0.7, 0.8],\n",
    "        'gamma': [0.1, 0.2],\n",
    "        'reg_lambda': [1, 1.5, 2, 3],  # Increased regularization\n",
    "        'reg_alpha': [0.1, 0.2, 0.3]\n",
    "    },\n",
    "    {\n",
    "        'n_estimators': [50, 100, 150],\n",
    "        'max_depth': [3, 4, None],\n",
    "        'min_samples_split': [2, 5, 10],\n",
    "        'min_samples_leaf': [1, 2, 4],\n",
    "        'max_features': ['auto', 'sqrt'],\n",
    "    },\n",
    "    {\n",
    "        'n_estimators': [50, 100, 150],\n",
    "        'learning_rate': [0.05, 0.1],\n",
    "        'max_depth': [3, 4],\n",
    "        'subsample': [0.7, 0.8],\n",
    "        'min_samples_split': [2, 5, 10],\n",
    "        'min_samples_leaf': [1, 2, 4],\n",
    "    },\n",
    "    {\n",
    "        'C': [0.1, 1, 10],\n",
    "        'kernel': ['linear', 'rbf'],\n",
    "        'gamma': ['scale', 'auto'] + [0.1, 0.2],\n",
    "    },\n",
    "    {\n",
    "        'penalty': ['l1', 'l2'],\n",
    "        'C': [0.1, 1, 10],\n",
    "    },\n",
    "    {\n",
    "        'n_neighbors': [3, 5, 7],\n",
    "        'weights': ['uniform', 'distance'],\n",
    "    }\n",
    "]\n",
    "\n",
    "# Initialize lists to store validation and test accuracies for each model\n",
    "validation_accuracies = []\n",
    "test_accuracies = []\n",
    "\n",
    "for model, param_grid in zip(models, param_grids):\n",
    "    # Setting up the GridSearchCV object with stratified K-Fold for the current model\n",
    "    grid_search = GridSearchCV(\n",
    "        estimator=model,\n",
    "        param_grid=param_grid,\n",
    "        cv=stratified_kfold,\n",
    "        verbose=1,\n",
    "        scoring='accuracy',\n",
    "        n_jobs=-1\n",
    "    )\n",
    "\n",
    "    # Performing the grid search\n",
    "    grid_search.fit(X_scaled, y)\n",
    "\n",
    "    # Best parameters and best score\n",
    "    print(f\"Best parameters found for {model.__class__.__name__}: \", grid_search.best_params_)\n",
    "    print(f\"Best cross-validated accuracy found for {model.__class__.__name__}: \", grid_search.best_score_)\n",
    "\n",
    "   \n",
    "    # Training the final model on the full training set using the best parameters\n",
    "    best_model = grid_search.best_estimator_\n",
    "    best_model.fit(X_train, y_train)\n",
    "\n",
    "    # Predicting on the test set with the best parameters\n",
    "    y_pred = best_model.predict(X_test)\n",
    "\n",
    "    # Calculating  the accuracy on the test set\n",
    "    test_accuracy = accuracy_score(y_test, y_pred)\n",
    "    print(f'Accuracy on the test set for {model.__class__.__name__}: {test_accuracy}')\n",
    "    \n",
    "    # Store validation and test accuracies\n",
    "    validation_accuracies.append(grid_search.best_score_)\n",
    "    test_accuracies.append(test_accuracy)\n",
    "\n",
    "# Plotting the accuracies\n",
    "plt.figure(figsize=(12, 6))\n",
    "models_names = [model.__class__.__name__ for model in models]\n",
    "plt.bar(models_names, validation_accuracies, label='Validation Accuracy', alpha=0.7)\n",
    "plt.bar(models_names, test_accuracies, label='Test Accuracy', alpha=0.7)\n",
    "plt.axhline(y=0.73, color='red', linestyle='--', label='Baseline (0.73)')\n",
    "plt.ylim(0, 1)\n",
    "plt.ylabel('Accuracy')\n",
    "plt.title('Validation and Test Accuracy Comparison')\n",
    "plt.legend()\n",
    "plt.show()\n"
   ]
  },
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   "cell_type": "code",
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   "id": "59fce836-933a-4a18-a40f-4f8e50dcc6a4",
   "metadata": {},
   "outputs": [],
   "source": []
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