Breast Cancer Prediction using Machine Learning

Problem Statement:

Breast cancer is one of the most common cancers among women worldwide, accounting for

approximately 25% of all cancer cases and affecting over 2.1 million individuals in 2015 alone.

Goal: Build a reliable machine learning model that classifies breast tumors as malignant or benign based

on clinical measurements and diagnostic features.

Dataset Description:

Source: Breast Cancer Dataset from Kaggle by Yasser H. Kaggle

Nature: This is a binary classification dataset containing tumor data, with attributes describing characteristics of

cell nuclei.

Why This Project Matters:

Early and accurate tumor detection can significantly improve treatment outcomes and patient survival.

Applying machine learning enhances diagnostic efficiency and reduces reliance on human interpretation.