Machine Learning Basic Calculator

Welcome to the Machine Learning Basic Calculator repository! This tool provides essential functionalities for evaluating and visualizing machine learning models, including PCA, performance metrics, and confusion matrix visualization.

Features

• PCA Visualization: Calculate and visualize Principal Component Analysis (PCA) for dimensionality reduction.
• Performance Metrics: Compute and display key metrics, including accuracy, precision, F1 score, and recall.
• Confusion Matrix: Generate and visualize the confusion matrix for model evaluation.
• Canvas Annotations: Draw and place labels on the canvas for enhanced data visualization.

Screenshots

Canvas and Performance Metrics Tables

Canvas and Confusion Matrix

Getting Started

To get started with the Machine Learning Basic Calculator, follow these steps:

1. Clone the Repository:

   git clone https://github.com/yourusername/machine-learning-basic-calculator.git

2. Navigate to the Project Directory:

   cd machine-learning-basic-calculator

3. Install Dependencies with Bun:

   Install Bun if you haven't already, then use it to install project dependencies:

   bun install

4. Run the Development Server with Vite:

   Start the Vite development server:

   bun run dev

5. Open the Application:

   Open your browser and navigate to http://localhost:3000 to view the application.

Contributing

We welcome contributions to improve this tool. If you would like to contribute, please follow these guidelines:

1. Fork the repository.
2. Create a new branch (git checkout -b feature/YourFeature).
3. Commit your changes (git commit -am 'Add new feature').
4. Push to the branch (git push origin feature/YourFeature).
5. Create a new Pull Request.

For detailed contribution guidelines, please refer to the CONTRIBUTING.md file.

Author

• Hasan Ahamed

Feel free to reach out to the author for any questions or suggestions.