Introvert vs Extrovert Predictor

Predict whether a person is an Introvert or an Extrovert based on social behavior and personality traits using multiple machine learning models.

Dataset

This dataset is part of the Kaggle Playground Series 2025 competition.

Try the Streamlit App here: Introvert vs Extrovert Predictor

Features:

• Time_spent_Alone → Hours spent alone.
• Stage_fear → Stage fear (Yes/No).
• Social_event_attendance → How often they attend social events.
• Going_outside → Frequency of going outside.
• Drained_after_socializing → Feeling drained after socializing (Yes/No).
• Friends_circle_size → Number of close friends.
• Post_frequency → How often they post online.
• Personality → Target column (Introvert/Extrovert).

Preprocessing

• Label encoding for categorical features.
• Iterative Imputer for missing values.
• Scaling: StandardScaler, RobustScaler, PowerTransformer (Yeo-Johnson).
• Outliers handled in Time_spent_Alone.

Models Trained

• Logistic Regression
• K-Nearest Neighbors
• Decision Tree
• Random Forest
• Extra Trees
• Gaussian Naive Bayes
• Bagging (Decision Tree)
• AdaBoost
• XGBoost
• LightGBM
• CatBoost

Evaluation metrics: Accuracy, Precision, Recall, F1-score.
Confusion matrices plotted for all models.

Best Model

The best performing model is selected automatically based on F1-score ('AdaBoost').

Usage

1. Clone the repository.
2. Install dependencies (scikit-learn, pandas, numpy, xgboost, lightgbm, catboost, plotly, seaborn, matplotlib).
3. Run the main notebook/script to preprocess data, train models, and generate predictions.

Files

• Files/*.pkl → Saved models, encoders, scalers, imputers, and results.