Human Personality Analysis & Classification

This project focuses on analyzing human personality traits and classifying individuals based on their behavioral responses and characteristics. Using a real-world dataset, I applied various data preprocessing techniques, explored feature relationships, and built multiple machine learning models (such as Logistic Regression, Random Forest, and XGBoost) to predict personality types. The pipeline includes exploratory data analysis (EDA), visualization, model comparison, and evaluation using accuracy, precision, recall, and F1-score. This classification system can be useful in areas like psychology, HR screening, and personalized marketing.