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Related Questions
- Can model-agnostic methods still provide actionable insights despite feature correlations?
- How do model-agnostic methods cope with a vast number of features?
- In what cases would model-agnostic techniques perform poorly compared to interpretable models that incorporate this structure?
- Do model-agnostic interpretation techniques benefit from dimensionality reduction?
- Are there ways to increase interpretability by utilizing hierarchical clustering on highly correlated sets of features in the source space?
- Does a highly dimensional vector provide valuable additional insights?
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