Permutation Importance: How Much Worse the Model Gets When a Column Is Shuffled
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Lessons in this course
- Baseline & Contributions: Explaining a Linear Score Feature by Feature Pro
- Coalitions: All Eight Feature Subsets & the Model Output for Each Pro
- Shapley Values: Marginal Contributions over Every Order & the Weighted Formula Pro
- Interactions: How Shapley Splits an Effect Two Features Create Together Pro
- Permutation Importance: How Much Worse the Model Gets When a Column Is Shuffled Pro
- Partial Dependence & ICE Curves: One Feature Across the Whole Fleet Pro
- Counterfactuals: The Smallest Change That Flips a Decision Pro
- The Explanation Report: Global vs Local, Stability & Limitations Pro