Breast cancer classification

This project focuses on breast cancer diagnosis by applying data preprocessing, visualization, encoding, and splitting techniques. It includes statistical analysis to understand the data and implements machine learning models like Linear Regression, SVM, Logistic Regression, and Random Forest to predict cancer types with performance evaluated using metrics like accuracy , Confusion matrix and Classification report. The goal was to enhance early detection and improve diagnostic accuracy.