Tumour Cell Binary Classification using Support Vector Machines

This Python program classifies tumour cell datapoints as benign or malignant using a Support Vector Machine (SVM) algorithm. The program extracts data from a cell_samples.csv, preprocesses it, trains a SVM model, and then uses the trained model to classify new data.

Getting Started

Prerequisites

• Python 3.x
• pandas
• scikit-learn

Installation

1. Clone the repository to your local machine:

git clone https://github.com/yourusername/SVM-cancer-cell-classification.git

2. Install the required libraries using pip:

pip install pandas scikit-learn

Usage

1. Run the main.py file to run the program.

Customization

You can customize the model architecture, hyperparameters, and other settings by modifying the code in the main.py file. You can also update the preprocessing steps in the main.py file according to your specific requirements.

Contributing

If you would like to contribute to this project, please follow the standard GitHub fork and pull request workflow.

Credits:

• Article: https://medium.com/@opemipo404/classifying-tumour-cells-with-support-vector-machines-838e6396a8da
• Tutorial: https://youtu.be/7sz4WpkUIIs

License

This project is licensed under the MIT License.

Contact

If you have any questions, suggestions, or issues, please feel fre to contact me at opethepope@gmail.com.