Feature ranking for multi-target regression

DOI10.1007/s10994-019-05829-8zbMath1472.68154OpenAlexW2971238384WikidataQ127311439 ScholiaQ127311439MaRDI QIDQ782468

Dragi Kocev, Sašo Džeroski, Matej Petković

Publication date: 27 July 2020

Published in: Machine Learning (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10994-019-05829-8

zbMATH Keywords

tree-based methodsrelieffeature rankingmulti-target regression

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Linear inference, regression (62J99) Learning and adaptive systems in artificial intelligence (68T05) Statistical ranking and selection procedures (62F07)

Related Items (1)

JGPR: a computationally efficient multi-target Gaussian process regression algorithm

Uses Software

• FORS
• ReliefF

Cites Work

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• First order regression
• Top-down induction of first-order logical decision trees
• Theoretical and empirical analysis of ReliefF and RReliefF
• Multi-target regression via input space expansion: treating targets as inputs
• Feature selection for data and pattern recognition
• An Algorithm for Finding Best Matches in Logarithmic Expected Time
• 10.1162/153244303322753616
• SVM Multiregression for Nonlinear Channel Estimation in Multiple-Input Multiple-Output Systems
• Extremely randomized trees
• Random forests

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