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Breast cancer classification project featuring eda, pca, t-sne analysis and several classifiaction algorithms ๐Ÿ“Š

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breast-cancer classification eda logistic-regression pca python scikit-learn seaborn xgboost t-sne

breast-cancer's Introduction

Breast Cancer: End-to-End Machine Learning Project

๐Ÿ“– About

The project comes as a deepening of the final work of my Bachelor in Mathematical Engineering @ Politecnico di Milano. It is meant to be a guide to any machine learning classification-project from beginning to end.

In this repository, I divided the work into three different stages:

Each section is self-explainatory and contains all the code to replicate the results.

๐Ÿ“Š Dataset

The breast cancer dataset is a classic and very easy-to-use binary classification dataset. Gathered are various physical information of the breast cells and whether these cells are benign or malignant cancer cells.

The dataset is available on uci machine learning repository, or on kaggle.

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