Comparing performance of feedforward neural nets and \(K\)-means for cluster-based market segmentation

DOI10.1016/S0377-2217(98)00170-2zbMath0963.91074OpenAlexW2022266106MaRDI QIDQ1296363

Harald Hruschka, Martin Natter

Publication date: 27 June 2001

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0377-2217(98)00170-2

zbMATH Keywords

neural networksmarketingcluster analysismarket segmentation\(K\)-means

Mathematics Subject Classification ID

Clustering in the social and behavioral sciences (91C20) Neural networks for/in biological studies, artificial life and related topics (92B20)

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Cites Work

• Self-organization and associative memory
• Comparative performance of the FSCL neural net and \(K\)-means algorithm for market segmentation
• Neural networks: A review from a statistical perspective. With comments and a rejoinder by the authors
• A study of the classification capabilities of neural networks using unsupervised learning: A comparison with \(K\)-means clustering
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