Por favor utiliza este link para citar o compartir este documento: http://repositoriodigital.academica.mx/jspui/handle/987654321/347377
Título: Modeling Comparisons for some Classification Methods, Bayesian, Neural and Traditional Cluster Techniques
Palabras clave: Multidisciplinarias (Ciencias Sociales)
Segmentation techniques
latent class modeling
training data
neural networks
K-means classification method
hierarchical classification method
Editorial: Universidad Autónoma del Estado de México
Descripción: 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.
Other Identifiers: http://www.redalyc.org/articulo.oa?id=10413200002
Aparece en las Colecciones:Calle14: revista de investigación en el campo del arte

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