Integration of self-organizing feature map and K-means algorithm for market segmentation

DOI10.1016/S0305-0548(01)00043-0zbMath0994.90084OpenAlexW1974808478MaRDI QIDQ1603342

R. Smith

Publication date: 11 July 2002

Published in: Computers \& Operations Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0305-0548(01)00043-0

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Marketing, advertising (90B60)

Related Items (4)

A clustering method to identify representative financial ratios ⋮ A case study of using the generalized K-harmonic means method in decision-making processes ⋮ A trend based investment decision approach using clustering and heuristic algorithm ⋮ Application of ant \(K\)-means on clustering analysis

Cites Work

• Validity studies in clustering methodologies
• Comparative performance of the FSCL neural net and \(K\)-means algorithm for market segmentation
• A study of the classification capabilities of neural networks using unsupervised learning: A comparison with \(K\)-means clustering
• Unnamed Item

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