Mobile User Behavior Analysis

Overview

This project analyzes mobile usage patterns and predicts user behavior class.

Workflow

1. Data loading and cleaning
2. Exploratory Data Analysis (EDA)
3. Feature scaling
4. Model training (Decision Tree, KNN)
5. Model comparison

Models Used

• Decision Tree
• K-Nearest Neighbors

Evaluation

Accuracy score comparison was used to determine best model.