k-best feature selection and ranking via stochastic approximation

Author:

Akman David V.,Malekipirbazari MiladORCID,Yenice Zeren D.ORCID,Yeo Anders,Adhikari NiranjanORCID,Wong Yong Kai,Abbasi BabakORCID,Gumus Alev TaskinORCID

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference71 articles.

1. Feature selection via binary simultaneous perturbation stochastic approximation;Aksakalli;Pattern Recognition Letters,2016

2. Feature selection using stochastic approximation with Barzilai and Borwein non-monotone gains;Aksakalli;Computers & Operations Research,2021

3. Delve: a dataset-driven scholarly search and analysis system;Akujuobi;ACM SIGKDD Explorations Newsletter,2017

4. Keel data-mining software tool: data set repository, integration of algorithms and experimental analysis framework;Alcalá-Fdez;Journal of Multiple-Valued Logic and Soft Computing,2011

5. An empirical study on wrapper-based feature ranking;Altidor,2009

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