Lung Cancer Detection with SVM and KMeans

This project leverages the Support Vector Machine (SVM) and KMeans algorithms to detect lung cancer from medical images and patient data. The application also provides a comparison between the two algorithms. The graphical user interface (GUI) is built using Tkinter.

Features

• Lung Cancer Detection: Detect lung cancer using SVM and KMeans algorithms.
• GUI: User-friendly interface developed with Tkinter.
• Algorithm Comparison: Compare the performance of SVM and KMeans algorithms.
• Sample Testing: Test the algorithms with provided sample data.

Technologies Used

• SVM (Support Vector Machine): Machine learning algorithm for classification.
• KMeans: Clustering algorithm.
• Tkinter: Python library for creating graphical user interfaces.
• Python: Programming language used for implementation.

Getting Started

To get a local copy up and running, follow these steps.

Prerequisites

• Python installed (version 3.6 or higher)
• Necessary Python libraries:

  pip install numpy pandas scikit-learn matplotlib tk

• Navigate to the project directory

 cd lung-cancer-detection-svm

Running the application

To start the aplication, run:

python main.py