New Fast Algorithms for Error Rate-Based Stepwise Variable Selection in Discriminant Analysis

DOI10.1137/S1064827596300784zbMath0968.68204OpenAlexW2031645100MaRDI QIDQ4509873

D. H. Coomans, S. Aeberhard, O. Y. de vel

Publication date: 19 October 2000

Published in: SIAM Journal on Scientific Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1137/s1064827596300784

zbMATH Keywords

classificationdimensionality reductionclassifier-based variable selection

Mathematics Subject Classification ID

Analysis of algorithms (68W40) Complexity and performance of numerical algorithms (65Y20)

Related Items (12)

Unnamed Item ⋮ Different approaches to fuzzy clustering of incomplete datasets ⋮ An extension to possibilistic fuzzy cluster analysis ⋮ Normality-based validation for crisp clustering ⋮ Linear boundary discriminant analysis ⋮ Polynomial-based radial basis function neural networks (P-RBF NNs) realized with the aid of particle swarm optimization ⋮ Cluster ensemble selection based on relative validity indexes ⋮ Variable selection in discriminant analysis based on the location model for mixed variables ⋮ An estimation algorithm using distance clustering of data. ⋮ Invariant optimal feature selection: A distance discriminant and feature ranking based solution ⋮ Direct variable selection for discrimination among several groups ⋮ Fuzzy rule based classification with FeatureSelector and modified threshold accepting

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