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CONTRIBUTING.md

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Contributing Guidelines

Overview

This repository focuses on research-oriented machine learning implementations. We welcome contributions that:

  • Implement novel machine learning algorithms
  • Improve existing implementations
  • Add theoretical explanations or mathematical derivations
  • Enhance documentation and testing
  • Fix bugs or optimize performance

Contribution Process

  1. Fork the repository
  2. Create a feature branch:
git checkout -b feature/your-feature-name
  1. Implement your changes following our coding standards
  2. Add tests for new functionality
  3. Update documentation as needed
  4. Submit a pull request

Code Standards

  • Clear, documented mathematical foundations
  • Efficient implementations with appropriate use of vectorization
  • Comprehensive docstrings and inline comments
  • Unit tests for all new functionality
  • Type hints for Python functions
  • PEP 8 compliance

Documentation Requirements

  • Mathematical derivations where applicable
  • Complexity analysis
  • Usage examples
  • References to relevant papers or resources

Pull Request Process

  1. Ensure all tests pass
  2. Update relevant documentation
  3. Add entry to CHANGELOG.md
  4. Request review from maintainers

Development Setup

# Create virtual environment
python -m venv venv
source venv/bin/activate  # or `venv\Scripts\activate` on Windows

# Install dependencies
pip install -r requirements.txt

# Run tests
python -m pytest

Questions and Discussion

Open an issue for:

  • Algorithm implementation discussions
  • Theoretical questions
  • Feature proposals
  • Bug reports

Code of Conduct

  • Focus on technical merit and scientific accuracy
  • Provide constructive feedback
  • Maintain professional communication
  • Respect intellectual property and cite sources appropriately