Breast Cancer Classification with Multi-layer Perceptron (MLP)

Project Overview

This project utilizes a Multi-layer Perceptron (MLP) model to classify tumors as malignant or benign based on the Breast Cancer Wisconsin dataset. The model is evaluated using 5-fold cross-validation and analyzed for overfitting through learning curves.

Key Outcomes

• Developed a Multi-layer Perceptron model for classification.
• Achieved high accuracy through rigorous evaluation.
• Analyzed learning curves to identify potential overfitting.

Tools Used

• Python
• sklearn
• NumPy
• Pandas
• Matplotlib

View the Code

Click the link below to view the full code and documentation for this project on GitHub:

View on GitHub