BASSUM: a Bayesian semi-supervised method for classification feature selection

DOI10.1016/j.patcog.2010.10.023zbMath1213.68517OpenAlexW2070562133MaRDI QIDQ621082

Zhifeng Hao, Zhenjie Zhang, Ruichu Cai

Publication date: 2 February 2011

Published in: Pattern Recognition (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.patcog.2010.10.023

zbMATH Keywords

feature selectionMarkov blanketconditional independence testsemi-supervisedstructured object

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Pattern recognition, speech recognition (68T10)

Related Items (3)

Simple strategies for semi-supervised feature selection ⋮ Causal gene identification using combinatorial V-structure search ⋮ An efficient semi-supervised representatives feature selection algorithm based on information theory

Uses Software

• TMG
• TETRAD

Cites Work

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• Structured machine learning: the next ten years
• Feature selection with dynamic mutual information
• Wrappers for feature subset selection
• A Bayesian method for the induction of probabilistic networks from data
• Gene selection for cancer classification using support vector machines

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