Ensemble clustering based on weighted co-association matrices: error bound and convergence properties

DOI10.1016/J.PATCOG.2016.10.017zbMath1429.68207OpenAlexW2538920018MaRDI QIDQ2290326

Vladimir Berikov, Igor Pestunov

Publication date: 27 January 2020

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

Full work available at URL: https://doi.org/10.1016/j.patcog.2016.10.017

zbMATH Keywords

error boundcluster validity indexlatent variable modelco-association matrixensemble sizehyperspectral image segmentationweighted clustering ensemble

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05) Computing methodologies for image processing (68U10)

Related Items (3)

Model and method for constructing a heterogeneous cluster ensemble ⋮ External clustering validity index based on chi-squared statistical test ⋮ Group approach to solving the tasks of recognition

Cites Work

• Unnamed Item
• Clustering aggregation by probability accumulation
• A clustering ensemble: two-level-refined co-association matrix with path-based transformation
• Cluster ensemble selection based on relative validity indexes
• Combining Pattern Classifiers
• Random forests

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