This project is designed to classify breast cancer as either Benign or Malignant using multiple machine learning models. The project includes data preprocessing, model training, evaluation, and deployment of the best-performing model.
The goal of this project is to create an efficient machine learning pipeline for the classification of breast cancer. Multiple classifiers are trained, and the best-performing model is saved for predictions on new data.
The dataset used for this project is breast_cancer_data_cleaned.csv, which contains preprocessed data with relevant features:
- Features include radiographic data, mean texture, mean perimeter, etc.
- Target column:
diagnosis(0 = Benign, 1 = Malignant).
To run this project, clone the repository and install the required dependencies using the requirements.txt file.
# Clone the repository
git clone (https://github.com/BCC-project/Breast-Cancer-classifications-.git)
# Navigate to the project directory
cd breast-cancer-classification
# Install dependencies
pip install -r requirements.txt