文章基本信息

标题：Modeling Comparisons for some Classification Methods, Bayesian, Neural and Traditional Cluster Techniques
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作者：Jean-Pierre Lévy Mangin ; Juan Antonio Moriano ; Normand Bourgault 等
期刊名称：Ciencia Ergo Sum
印刷版ISSN：1405-0269
出版年度：2010
卷号：17
期号：2
页码：127-135
语种：English
出版社：Universidad Autónoma del Estado de México
摘要：This article compares some classification methods that would be very useful for clustering purposes mainly in marketing. First of them are based on Latent Class Mixture Modeling with training data and without training data. The second set of techniques is based on Neural Networks Classification Method and finally we will present methods based on more classical techniques like K-Means and Hierarchical Cluster Analysis techniques.
其他摘要：This article compares some classification methods that would be very useful for clustering purposes mainly in marketing. First of them are based on Latent Class Mixture Modeling with training data and without training data. The second set of techniques is based on Neural Networks Classification Method and finally we will present methods based on more classical techniques like K-Means and Hierarchical Cluster Analysis techniques.
关键词：Segmentation techniques; latent class modeling; training data; neural networks; K-means classification method; hierarchical classification method. Técnicas d...