GAPS: A clustering method using a new point symmetry-based distance measure

DOI10.1016/j.patcog.2007.03.026zbMath1122.68486OpenAlexW2045848691MaRDI QIDQ996422

Sriparna Saha, Sanghamitra Bandyopadhyay

Publication date: 14 September 2007

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

Full work available at URL: https://doi.org/10.1016/j.patcog.2007.03.026

zbMATH Keywords

symmetrygenetic algorithmunsupervised classificationKd-treepoint symmetry-based distance

Mathematics Subject Classification ID

Nonnumerical algorithms (68W05) Learning and adaptive systems in artificial intelligence (68T05) Pattern recognition, speech recognition (68T10)

Related Items

A symmetry based multiobjective clustering technique for automatic evolution of clusters ⋮ Use of symmetry and stability for data clustering ⋮ Reference point based archived many objective simulated annealing ⋮ An unsupervised learning algorithm for membrane computing ⋮ A robust dynamic niching genetic algorithm with niche migration for automatic clustering problem ⋮ Quantization-based clustering algorithm ⋮ PCA image coding with iterative clustering ⋮ \(K\)-means cloning: adaptive spherical \(K\)-means clustering ⋮ A new point symmetry based fuzzy genetic clustering technique for automatic evolution of clusters ⋮ Enhancing point symmetry-based distance for data clustering ⋮ GAPS

Uses Software

• J-MEANS
• ANN

Cites Work

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