{"slug":"jaechang-hits-shap-model-explainability","source_name":"jaechang-hits/shap-model-explainability","name":"Jaechang Hits/Shap Model Explainability","description":"Model interpretability via SHAP (Shapley values from game theory). Covers explainer choice (Tree, Deep, Linear, Kernel, Gradient, Permutation), feature attribution, and plots (waterfall, beeswarm, bar, scatter, force, heatmap). Use to explain ML predictions, rank features, debug models, audit fairness, or compare models. Works with tree, deep, linear, and black-box models.","version":1,"lift":{"pass_rate_delta_pts":4.55,"pass_rate_pct":100,"total_cases":22,"passed_cases":22,"tokens_delta_pct":305.3,"turns_delta_pct":0,"verdict":"pass","benchmark_model":"gemini-3.6-flash","grading_method":"judged","completed_at":"2026-08-23T23:21:55.484561+00:00"},"skill_score":1,"benchmark_models":[{"model":"gemini-3.6-flash","headline":true,"delta_pts":4.55,"with_pass_pct":100,"without_pass_pct":95.5,"tokens_delta_pct":305.3,"turns_delta_pct":0,"total_cases":22,"cases_aggregated":22,"verdict":"pass","never_hurt":true,"completed_at":"2026-08-23T23:21:55.484561+00:00","run_id":"016977e2-6529-406f-9793-5a6d845f725d","version_number":1,"is_latest_version":true,"gate":null}],"trust":{"skill_safety":"passed","safety_status":"clean","intent_verdict":"safe","content_status":"clean","indexable":true},"license":"MIT","install_count":0,"manifest_hash":"8dd0016a664b6415478438a7f2986ecfb6191b5678a46cea486383c2356e21f2","raw_url":"https://app.decimal.ai/s/jaechang-hits-shap-model-explainability/SKILL.md","scorecard_url":"https://app.decimal.ai/skills/jaechang-hits-shap-model-explainability"}