Constrained classification: The use of a priori information in cluster analysis

DOI10.1007/BF02294172zbMath0554.62050OpenAlexW1967425904MaRDI QIDQ760129

Vijay Mahajan, Wayne S. Desarbo

Publication date: 1984

Published in: Psychometrika (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf02294172

zbMATH Keywords

constrained optimizationclusteringCONCLUSconstrained classification

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Monte Carlo methods (65C05)

Related Items (11)

A survey of constrained classification ⋮ A survey on feature weighting based K-means algorithms ⋮ Least squares algorithms for constructing constrained ultrametric and additive tree representations of symmetric proximity data ⋮ Local labour markets delineation: an approach based on evolutionary algorithms and classification methods ⋮ A note on the formal implementation of the \(K\)-means algorithm with hard positive and negative constraints ⋮ Mixtures of (constrained) ultrametric trees ⋮ A hierarchical Bayesian procedure for two-mode cluster analysis ⋮ A maximum likelihood methodology for clusterwise linear regression ⋮ A constrained \(k\)-means clustering algorithm for classifying spatial units ⋮ A modified \(k\)-means clustering procedure for obtaining a cardinality-constrained centroid matrix ⋮ Optimal variable weighting for hierarchical clustering: An alternating least-squares algorithm

Uses Software

• Indclus

Cites Work

• Synthesized clustering: A method for amalgamating alternative clustering bases with differential weighting of variables

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