Three-objective constrained evolutionary instance selection for classification: Wrapper and filter approaches-Reference-Cited by-同舟云学术

Three-objective constrained evolutionary instance selection for classification: Wrapper and filter approaches

Published:2022-01 Issue: Volume:107 Page:104531
ISSN:0952-1976
Container-title:Engineering Applications of Artificial Intelligence
language:en
Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Jiménez Fernando,Sánchez Gracia,Palma José,Sciavicco Guido^ORCID

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Artificial Intelligence,Control and Systems Engineering

Reference107 articles.

1. A multi-objective evolutionary approach to training set selection for support vector machine;Acampora;Knowl. Based Syst.,2018

2. Instance-based learning algorithms;Aha;Mach. Learn.,1991

3. KEEL data-mining software tool: Data set repository, integration of algorithms and experimental analysis framework;Alcalá-Fdez;J. Mult.-Valued Logic Soft Comput.,2010

4. Learning with many irrelevant features;Almuallim,1991

5. Fusion of instance selection methods in regression tasks;Arnaiz-González;Inf. Fusion,2016

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