Feature Importance Analyzer

소개

The Feature Importance Analyzer is a specialized Claude Code skill designed to streamline the model evaluation phase of machine learning projects. It provides automated, step-by-step guidance for calculating and interpreting feature importance across various frameworks like PyTorch, TensorFlow, and Scikit-learn. By integrating industry best practices, the skill helps developers identify redundant features, optimize model training, and generate production-ready analysis code, making complex data insights accessible through simple natural language commands during the ML training workflow.

주요 기능

• Automated feature importance calculation for multiple ML frameworks
• Step-by-step guidance on feature selection and model pruning
• Validation of outputs against common data science standards
• Deep integration with PyTorch, TensorFlow, and Scikit-learn
• 1,063 GitHub stars
• Generation of production-ready evaluation and analysis scripts

사용 사례

• Explaining model decisions to stakeholders by identifying key variables
• Optimizing model performance by removing redundant or noisy features
• Debugging unexpected model behavior during the training phase