Breast Cancer Diagnosis Prediction

A logistic regression model to predict whether a breast tumor is benign or malignant using the Wisconsin Diagnostic Breast Cancer (WDBC) dataset.

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📌 Overview

• Dataset: 569 samples, 30 features (e.g., radius, texture, perimeter).
• Model: Logistic regression with L2 regularization and gradient descent.
• Performance:
  • Training Accuracy: 97.36%
  • Test Accuracy: 96.49%

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🚀 How to Use

Prerequisites

• Python 3.8+
• Required libraries: numpy, pandas, matplotlib, seaborn, scikit-learn

Install dependencies:

pip install numpy pandas matplotlib seaborn scikit-learn

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⚠️ Disclaimer

This model is for educational purposes only and not a substitute for professional medical advice.