HealthyData-Hub / Diagnosis-of-Breast-Cancer

To utilize the Breast Cancer Wisconsin Dataset for machine learning purposes. The aim is to diagnose breast cancer by employing a supervised binary, distance-based classifier (K Nearest Neighbours), which will classify cases as either benign or malignant.

Diagnosis of Breast Cancer

Description

This project focuses on diagnosing breast cancer using binary, supervised machine learning. It utilizes a distance-based algorithm, specifically the k-Nearest Neighbors (KNN) algorithm. The project employs a robust 5-fold nested cross-validation technique for model evaluation and hyper-parameter tuning.

Installation

1. Clone the repository: git clone https://github.com/your-username/diagnosis-of-breast-cancer.git
2. Navigate to the project directory: cd diagnosis-of-breast-cancer
3. Install required dependencies: pip install -r requirements.txt

Usage

1. Ensure your dataset is appropriately formatted.
2. Modify the necessary parameters in the script.
3. Run the main script: python main.py

Contributing

Contributions are welcome! Please follow the guidelines in the GitHub CONTRIBUTING.md.

License

This project is licensed under the APACHE 2.0 LICENSE.

Contact

For questions, suggestions, or feedback, feel free to reach out to us - refer to details in our profile