Breast Cancer Pattern Recognition through Association Rule Mining

Overview

This project, affiliated with Islamic Azad University, involves utilizing association rule mining techniques to analyze patterns and relationships within breast cancer data. The goal is to enhance the detection and understanding of factors associated with breast cancer.

Features

• Association Rule Mining: Utilizes advanced data mining techniques to analyze patterns within breast cancer data.
• Pattern Recognition: Aims to recognize and understand patterns associated with breast cancer.
• Enhanced Detection: Contributes to the enhancement of breast cancer detection by identifying significant relationships in the data.

Objectives

• Apply association rule mining techniques to identify patterns and relationships in breast cancer data.
• Improve the understanding of factors associated with breast cancer for enhanced detection and diagnosis.

Affiliation

This project is associated with Islamic Azad University. For more information, visit University Website.

Getting Started

Prerequisites

• Checkout requirements.txt

Installation

1. Clone the repository:

   git clone https://github.com/your-username/breast-cancer-pattern-recognition.git

2. Install dependencies:

   pip install requirements.txt

Contributors

• SMB H
• Parastou Alayi
• Mir Yousef Hosseini
• Sajedeh Akrami

License

This project is licensed under the BSD-3 - see the LICENSE file for details.