Novel soft subspace clustering with multi-objective evolutionary approach for high-dimensional data

DOI10.1016/j.patcog.2013.02.005zbMath1323.68449OpenAlexW2069046167WikidataQ115441863 ScholiaQ115441863MaRDI QIDQ888558

Dehong Yu, Jian Zhuang, Hu Xia

Publication date: 30 October 2015

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

Full work available at URL: https://doi.org/10.1016/j.patcog.2013.02.005

zbMATH Keywords

multi-objective evolutionary algorithmsubspace clusteringdetermination of the best solutiondetermination of the cluster number

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) (68T20)

Related Items

Transfer learning-assisted multi-objective evolutionary clustering framework with decomposition for high-dimensional data, Multi-objective soft subspace clustering in the composite kernel space, Enhanced soft subspace clustering through hybrid dissimilarity, Multimode process monitoring based on data-driven method, A fast multiobjective fuzzy clustering with multimeasures combination

Uses Software

• Silhouettes
• MOCK

Cites Work

• Unnamed Item
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• Enhanced soft subspace clustering integrating within-cluster and between-cluster information
• 10.1162/153244303321897735