Ensemble feature selection using election methods and ranker clustering
type: Item
instance of: scholarly article
title: Ensemble feature selection using election methods and ranker clustering
zbMATH Open document ID: 1443.68146
author: Peter Drotár
author: Matej Gazda
author: Liberios Vokorokos
published in: Information Sciences
publication date: 2020-10-07T00:00:00Z
Mathematics Subject Classification ID: 68T05
Mathematics Subject Classification ID: 62H30
Mathematics Subject Classification ID: 91B12
zbMATH DE Number: 7257010
zbMATH Keywords: feature selection
zbMATH Keywords: ensemble
zbMATH Keywords: voting
zbMATH Keywords: mean-shift clustering
zbMATH Keywords: Borda count
describes a project that uses: Scikit
describes a project that uses: AdaBoost-SAMME
describes a project that uses: ReliefF
MaRDI profile type: Publication
full work available at URL: j.ins.2018.12.033
OpenAlex ID: W2906662890
cites work: Breaking the Curse of Dimensionality with Convex Neural Networks
cites work: Single transferable vote resists strategic voting
cites work: Q3286740
cites work: Wrappers for feature subset selection
cites work: Q5396710
cites work: Theoretical and empirical analysis of ReliefF and RReliefF
cites work: Multi-class AdaBoost
DOI: 10.1016/J.INS.2018.12.033
description: scientific article; zbMATH DE number 7257010