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Linear Regression MCP

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Train a Linear Regression model by uploading a CSV dataset file, demonstrating an end-to-end machine learning workflow.

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Linear Regression MCP

Welcome to Linear Regression MCP! This project demonstrates an end-to-end machine learning workflow using Claude and the Model Context Protocol (MCP).

Claude can train a Linear Regression model entirely by itself, simply by uploading a CSV file containing the dataset. The system goes through the entire ML model training lifecycle, handling data preprocessing, training, and evaluation (RMSE calculation).


Available Tools

The following tools are available in this project to help you work with the dataset and train the model:

ToolDescriptionArguments
upload_file(path)Uploads a CSV file and stores it for processing.path: Absolute path to the CSV file.
get_columns_info()Retrieves the column names in the uploaded dataset.No arguments.
check_category_columns()Checks for any categorical columns in the dataset.No arguments.
label_encode_categorical_columns()Label encodes categorical columns into numerical values.No arguments.
train_linear_regression_model(output_column)Trains a linear regression model and calculates RMSE.output_column: The name of the target column.

Open for Contributions

I welcome contributions to this project! Whether it's fixing bugs, adding new features, or improving the documentation, feel free to fork the repository and submit pull requests.

If you have any suggestions or feature requests, open an issue, and I'll be happy to discuss them!

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