Feature Importance in Gradient Boosting Trees with Cross-Validation Feature Selection

Gradient Boosting Machines (GBM) are among the go-to algorithms on tabular data, which produce state-of-the-art results in many prediction tasks. Despite its popularity, the GBM framework suffers from a fundamental flaw in its base learners. Specifically, most implementations utilize decision trees...

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Bibliografski detalji

Glavni autori:	Afek Ilay Adler, Amichai Painsky
Format:	Artigo
Jezik:	Inglês
Izdano:	MDPI AG 2022-05-01
Serija:	Entropy
Teme:	gradient boosting feature importance tree-based methods classification and regression trees
Online pristup:	https://www.mdpi.com/1099-4300/24/5/687
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