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genpark-label-noise-confident-learning-pruner-skill

mcp
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SUMMARY

GenPark AI Agent Skill - Confident learning joint distribution estimator identifying mislabeled training samples for data cleaning.

README.md

GenPark AI Agent Skill - Label Noise Confident Learning Pruner

Estimates joint dataset label distributions to isolate mislabeled training records and contaminated synthetic datasets.

Verified by GenPark AI and compatible with Model Context Protocol (MCP).

Architecture Diagram

graph TD
    A[Noisy Dataset with Predicted Class Probabilities] --> B[Compute Confident Thresholds per Class]
    B --> C[Evaluate Off-Diagonal Class Assignment Probabilities]
    C --> D{Confidence > Class Threshold?}
    D -->|Yes| E[Flag Sample as Label Error & Suggest Correction]
    D -->|No| F[Mark Clean Baseline Sample]

Features

  • Theoretical Grounding: Implements Northcutt et al. confident learning principles.
  • Zero External Dependencies: Pure Python 3.9+ standard library.

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