This repository contains a Python-based pipeline for analyzing and classifying behavioral data using machine learning and deep learning models. The project demonstrates the application of a Random Forest Classifier and a Neural Network to classify individuals into behavioral groups based on the provided dataset.
- Data Preprocessing: Cleans and standardizes the dataset, handling missing values and categorical transformations.
- Machine Learning: Implements a Random Forest Classifier for group classification.
- Deep Learning: Utilizes a Neural Network model with Keras for advanced classification.
- Evaluation: Provides metrics like accuracy, confusion matrix, classification report, and AUC-ROC curves for performance analysis.
- Visualization: Includes training history plots and AUC-ROC curves for interpretability.
Before running the code, ensure you have the following installed:
- Python 3.7+
- TensorFlow 2.x
- Scikit-learn
- Pandas
- NumPy
- Matplotlib