Comparing performance of feedforward neural nets and K-means for cluster-based market segmentation
作者： Harald Hruschka , Martin Natter
DOI: 10.1016/S0377-2217(98)00170-2
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摘要: We compare the performance of a specifically designed feedforward artificial neural network with one layer hidden units to K-means clustering technique in solving problem cluster-based market segmentation. The data set analyzed consists usages brands (product category: household cleaners) different usage situations. proposed model results two segment solution that is confirmed by appropriate tests. On other hand, algorithm fails discovering any somewhat stronger cluster structure. Classification respondents on basis external criteria better for solution. also demonstrate managerial interpretability results.
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