This project classifies breast cancer tumors as benign or malignant using the Random Forest algorithm.
The dataset used is the Breast Cancer Wisconsin (Diagnostic) Dataset from scikit-learn.
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.
- Clone the repository:
git clone https://github.com/CodeByGirum/Breast-Cancer-Classification-Model-using-RF.git cd Breast-Cancer-Classification-Model-using-RF