Nonlinear multicriteria clustering based on multiple dissimilarity matrices

DOI10.1016/j.patcog.2013.06.008zbMath1326.68250OpenAlexW4298054584MaRDI QIDQ898226

Sergio Queiroz, Yves Lechevallier, Francisco de. A. T. de Carvalho

Publication date: 8 December 2015

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

Full work available at URL: https://doi.org/10.1016/j.patcog.2013.06.008

zbMATH Keywords

nonlinear optimizationrelational datamulticriteria decision supportclustering analysis

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05) Pattern recognition, speech recognition (68T10)

Uses Software

• UCI-ml

Cites Work

• Partitioning hard clustering algorithms based on multiple dissimilarity matrices
• Similarity of personal preferences: Theoretical foundations and empirical analysis
• Handling multicriteria preferences in cluster analysis
• On the completeness and constructiveness of parametric characterizations to vector optimization problems
• Towards multicriteria clustering: an extension of the \(k\)-means algorithm
• Clustering and aggregation of relational data with applications to image database categorization
• On Central Tendency and Dispersion Measures for Intervals and Hypercubes
• A non-classical logic for information retrieval
• Finding Groups in Data
• An interactive weighted Tchebycheff procedure for multiple objective programming
• Smoothed Analysis of the k-Means Method
• The elements of statistical learning. Data mining, inference, and prediction
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