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Machine Learning Algorithms

This repository contains implementations of various machine learning algorithms, organized into categories such as classification, clustering, regression, and more. The project is designed to provide a hands-on understanding of machine learning concepts and their practical applications.

Table of Contents

Project Structure

The repository is organized as follows:

MachineLearningLab/
├── src/
│   ├── Classification/      # Algorithms related to classification tasks
│   ├── Clustering/          # Algorithms related to clustering tasks
│   ├── DataUtils/           # Utilities for data preprocessing and handling
│   ├── Evaluation/          # Tools for evaluating model performance
│   ├── Regression/          # Algorithms related to regression tasks
│   ├── Utils/               # General utility functions
│   ├── MainForm.cpp         # Main application logic
│   ├── MainForm.h           # Header file for the main form
│   ├── MainForm.resx        # Resource file for the main form
│   └── .DS_Store            # System file (can be ignored)

Features

  • Classification: Implementation of classification algorithms like Decision Trees, SVMs, etc.
  • Clustering: Includes algorithms such as K-Means and Hierarchical Clustering.
  • Regression: Covers linear regression and other regression techniques.
  • Evaluation: Provides tools to measure model performance (e.g., accuracy, precision).
  • Data Utilities: Functions for data preprocessing like normalization, splitting datasets, etc.

Installation

  1. Clone the repository: 
    git clone https://github.com/hamarshehmhmd/Machine_Learning_Algorithms.git
  2. Navigate to the project directory: 
    cd Machine_Learning_Algorithms/MachineLearningLab/src/
  3. Ensure you have the required dependencies installed (if applicable).

Usage

  1. Open the project in your preferred IDE or text editor.
  2. Navigate to the desired folder (e.g., Classification, Clustering) to explore specific algorithms.
  3. Run the MainForm.cpp file to launch the main application interface.

Contributing

Contributions are welcome! If you'd like to contribute:

  1. Fork this repository.
  2. Create a new branch: 
    git checkout -b feature-name
  3. Commit your changes: 
    git commit -m "Add a new feature"
  4. Push to your branch: 
    git push origin feature-name
  5. Submit a pull request.

License

This project is licensed under the MIT License. See the LICENSE file for details.