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Quantitative Finance · Glossary

What is Substitution effect, clustered feature importance?

Also known as: substitution effect · clustered feature importance

Definition 6.6 Machine Learning for Markets · Chapter 6 — Feature Engineering, Selection and Importance

The substitution effect is the understatement of a feature’s importance when a correlated feature can stand in for it: permuting or dropping one leaves the other. Clustered feature importance measures importance for groups of correlated features, permuted or dropped together, the groups found by hierarchical clustering on 1−∣correlation∣1 - |\text{correlation}| (López de Prado, 2020).

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