This repository contains a machine learning model to predict whether a patient has breast cancer based on various features such as radius, texture, perimeter, etc. The model is trained using the Wisconsin Breast Cancer dataset and the Jupyter Notebook contains the code for training the model, making predictions and evaluating its performance.
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.
You need to have the following packages installed on your system:
- NumPy
- Pandas
- Matplotlib
- Sklearn
- Seaborn
You can install them by running the following command in your terminal:
pip install numpy pandas matplotlib sklearn seaborn
Clone the repository to your local machine:
git clone https://github.com/chandramohan0/BreastCancerPrediction.git
The model can be run using the Jupyter Notebook BreastCancerPrediction.ipynb. The code will load the Wisconsin Breast Cancer dataset, train the model, make predictions and evaluate its performance.
- NumPy - A library for the Python programming language, adding support for large, multi-dimensional arrays and matrices.
- Pandas - A library for the Python programming language, providing easy-to-use data structures and data analysis tools.
- Matplotlib - A plotting library for the Python programming language.
- Sklearn - A machine learning library for the Python programming language.
- Seaborn - A data visualization library based on Matplotlib.
If you'd like to contribute to this repository, please open a pull request. Any contributions are welcome!