This repository contains code and resources for a breast cancer classification project. The goal of this project is to develop a model that can accurately classify breast cancer tumors as either benign or malignant.
The dataset used for this project is the Winston dataset, a well-known dataset widely used in breast cancer research. It contains a collection of features extracted from breast mass images, along with their corresponding labels indicating whether the tumor is benign or malignant.
To run the code in this repository, you need the following dependencies:
- Python (version 3.6 or higher)
- NumPy
- Pandas
- Scikit-learn
- Matplotlib
- SeaBorn
You can install the required dependencies using pip:
pip install numpy pandas scikit-learn matplotlib seaborn
- Clone the repository to your local machine:
git clone https://github.com/cyblogerz/Breast-cancer-classification.git
- Change into the project directory:
cd breast-cancer-classification
- Run the
breast_cancer_classification.ipynbnotebook using Jupyter Notebook or Jupyter Lab to see the implementation and results of the breast cancer classification model.