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Breast Cancer Classification Model using RF

This project classifies breast cancer tumors as benign or malignant using the Random Forest algorithm.

Dataset

The dataset used is the Breast Cancer Wisconsin (Diagnostic) Dataset from scikit-learn.

Methods and Result

I developed the model to classify breast cancer tumors as either benign or malignant using a dataset with 569 samples. I split the data into training (80%) and testing (20%) sets. Initially, the model achieved 95.61% accuracy. After fine-tuning, the accuracy improved to 97.39%. The model now has a precision of 98% for benign and 96% for malignant tumors, with a recall of 97% for benign and 98% for malignant tumors. This shows significant improvement in identifying both types of tumors accurately.

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Setup

  1. Clone the repository: 
    git clone https://github.com/CodeByGirum/Breast-Cancer-Classification-Model-using-RF.git
cd Breast-Cancer-Classification-Model-using-RF