概要
This skill empowers Claude to demystify black-box machine learning models by providing clear, actionable insights into model behavior and prediction logic. By leveraging advanced techniques like SHAP (SHapley Additive exPlanations) and LIME (Local Interpretable Model-agnostic Explanations), it allows developers and data scientists to identify key feature influencers, debug unexpected model performance, and ensure algorithmic fairness. Whether you are investigating a specific prediction or auditing overall model transparency, this skill translates complex statistical data into understandable explanations for both technical teams and stakeholders.
