A new approach to classification

R. Fuentes-Garcia; S.G. Walker

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A new approach to classification

机译：一种新的分类方法

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摘要

Clustering is a common and important issue, and finite mixture models based on the normal distribution are frequently used to address the problem. In this article, we consider a classification model and build a mixture model around it. A good assessment of the allocation of observations and number of clusters is easily obtained from this approach.

机译：聚类是一个常见且重要的问题，基于正态分布的有限混合模型通常用于解决该问题。在本文中，我们考虑一个分类模型并围绕它建立一个混合模型。通过这种方法很容易获得对观测值分配和聚类数量的良好评估。

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来源
《Journal of applied statistics》 |2010年第2期|137-146|共10页
作者
R. Fuentes-Garcia; S.G. Walker;
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作者单位

Facultad de Ciencias, Universidad National Autonoma de Mexico, Mexico, DF 04510, Mexico;

Institute of Mathematics, Statistics and Actuarial Science, University of Kent, Canterbury, Kent, CT2 7NZ, UK;

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正文语种 eng
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关键词
clustering; classification; latent variable; normal mixture-model; random histogram;

机译：集群分类;潜变量普通混合模型随机直方图;

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A new approach to classification

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