Description
Developed and evaluated machine learning models to detect malware in Android applications, focusing on maximizing precision and recall. Built and compared multiple XGBoost models using different feature sets, analyzing performance with F1 score, precision, recall, confusion matrices, and precision-recall curves. The most comprehensive model, leveraging all available features, achieved strong results in identifying malicious apps.