Saved in:
| Main Author: | |
|---|---|
| Format: | Artículo científico |
| Language: | en |
| Published: |
Universidad Autónoma del Estado de México
2010
|
| Subjects: | |
| Online Access: | https://www.redalyc.org/articulo.oa?id=10413200002 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Table of Contents:
- Modeling Comparisons for some Classification Methods, Bayesian, Neural and Traditional Cluster Techniques Jean-Pierre Lévy Mangin Juan Antonio Moriano Normand Bourgault Multidisciplinarias (Ciencias Sociales) training data neural networks latent class modeling Segmentation techniques means classification method 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. 2010 artículo científico 1405-0269 https://www.redalyc.org/articulo.oa?id=10413200002 en http://www.redalyc.org/revista.oa?id=104 CIENCIA ergo-sum, Revista Científica Multidisciplinaria de Prospectiva application/pdf Universidad Autónoma del Estado de México CIENCIA ergo-sum, Revista Científica Multidisciplinaria de Prospectiva (México) Num.2 Vol.17