Least loss: a simplified filter method for feature selection

DOI10.1016/J.INS.2020.05.017zbMath1459.68177OpenAlexW3028308428MaRDI QIDQ2023188

Fadi Thabtah, Firuz Kamalov, Suhel Hammoud, Seyed Reza Shahamiri

Publication date: 3 May 2021

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2020.05.017

zbMATH Keywords

classificationdata miningmachine learningdimensionality reductionfeature selectionranking of variablesinformation science

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05)

Related Items (1)

Dependency maximization forward feature selection algorithms based on normalized cross-covariance operator and its approximated form for high-dimensional data

Uses Software

• UCI-ml
• C4.5

Cites Work

• Maximum weight and minimum redundancy: a novel framework for feature subset selection
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