This repository contains implementations of various supervised learning algorithms. Each algorithm is designed to solve different types of problems and can be used for tasks such as classification and regression.
📋 Algorithms Included
The following supervised learning algorithms are implemented in this repository:
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🌳 Decision Trees: A popular algorithm that uses a tree-like model to make decisions based on features.
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📈 Linear Regression: A simple yet powerful algorithm that models the relationship between a dependent variable and one or more independent variables.
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🌿 Random Forest: An ensemble algorithm that combines multiple decision trees to make more accurate predictions.
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📊 Logistic Regression: A binary classification algorithm that models the probability of a certain event occurring.
🛠️ Usage
Run the algorithm on your dataset by executing the main script or Jupyter notebook.
🤝 Contributing Contributions are welcome! If you'd like to contribute to this repository, please follow these guidelines: Fork the repository. Create a new branch for your feature or bug fix. Commit your changes and push them to your branch. Submit a pull request explaining your changes and why they should be merged.
Thank you for using this repository! We hope you find these supervised learning algorithms useful for your projects. 😊