Feature selection for multi-label naive Bayes classification
type: Item
instance of: scholarly article
title: Feature selection for multi-label naive Bayes classification
zbMATH Open document ID: 1193.68219
author: Min-Ling Zhang
author: Jose M. Peña
author: Víctor Robles
published in: Information Sciences
publication date: 2009-10-01T00:00:00Z
Mathematics Subject Classification ID: 68T05
Mathematics Subject Classification ID: 68T10
zbMATH DE Number: 5610246
zbMATH Keywords: multi-label learning
zbMATH Keywords: naive Bayes
zbMATH Keywords: feature selection
zbMATH Keywords: principal component analysis
zbMATH Keywords: genetic algorithm
describes a project that uses: C4.5
describes a project that uses: ML-KNN
describes a project that uses: BoosTexter
MaRDI profile type: Publication
full work available at URL: j.ins.2009.06.010
OpenAlex ID: W1970696760
cites work: Q4802571
cites work: Q4436417
cites work: Q4139463
cites work: Q4692508
cites work: Q3093406
cites work: BoosTexter: A boosting-based system for text categorization
cites work: Degrees of conditional (in)dependence: A framework for approximate Bayesian networks and examples related to the rough set-based feature selection
cites work: Decision trees for hierarchical multi-label classification
cites work: ML-KNN: A lazy learning approach to multi-label learning
DOI: 10.1016/J.INS.2009.06.010
description: scientific article; zbMATH DE number 5610246