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MCP Machine Learning Agent

MCP Machine Learning Agent

by aparnanaredla5-cell
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    • MCP Machine Learning Agent

      Greeshma-19
      A
      license
      Not graded
      quality
      C
      maintenance
      Enables users to train and compare Logistic Regression and KNN models on the Wisconsin breast cancer dataset, run predictions on patient feature inputs, compute confusion-matrix metrics and select the best model by malignant recall, generate global and local SHAP explanations, and export Parquet audit logs of every tool call. Also provides sample test-set inputs so agents can invoke prediction tools with valid 30-feature payloads.
      GPL 3.0

    • MCP Machine Learning Agent

      gowthamganta0207-creator
      A
      license
      A
      quality
      B
      maintenance
      Exposes MCP tools that train, evaluate, compare and explain Logistic Regression and KNN models on the Wisconsin breast cancer dataset, then serve malignant/benign predictions with SHAP explanations and a Parquet audit log of every call. It also provides ready-to-use sample patient inputs and model-selection tooling so agents can run a full ML workflow through natural language.
      9
      GPL 3.0

    • MCP Machine Learning Agent

      akhila7842
      A
      license
      Not graded
      quality
      C
      maintenance
      Enables training and comparing Logistic Regression and KNN models, retrieving sample patient inputs, predicting malignant or benign cases, evaluating metrics, selecting the best model, generating SHAP explanations, and exporting a Parquet audit log through MCP tools.
      GPL 3.0

    • MCP Machine Learning Agent

      pranavvenkata77-ship-it
      A
      license
      A
      quality
      B
      maintenance
      Enables training and comparing Logistic Regression and KNN models, generating sample patient inputs, making malignant/benign predictions, evaluating confusion-matrix metrics, selecting the best model, producing SHAP explanations, and exporting Parquet audit logs through MCP tools.
      9
      GPL 3.0

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