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Breast Cancer Prediction with ML

This project aims to develop machine learning models to predict breast cancer using patient data. The models classify the cancer as malignant or benign based on features extracted from medical scans.

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Project Overview

Breast cancer prediction is a significant problem in medical data analysis. This project uses a dataset of diagnostic features to train machine learning models that can classify cancer types. The project is built with Python and libraries such as Scikit-learn, Pandas, Matplotlib, and Seaborn to preprocess data, train models, and visualize results.

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This repository contains implementations of machine learning models for predicting cancer diagnoses. It includes Decision Tree and Support Vector Machine (SVM) classifiers with hyperparameter tuning, PCA-based dimensionality reduction, and decision boundary visualizations.

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