DETAILED CLASSIFICATION PROBLEM

机译：详细的分类问题

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The classification problem is concerned with allocation of new observations on several variables to two or more distinct categories known to exist a priori, on the basis of some pre-solved cases. Most of the existing solutions to the problem lack detailed inference with respect to the outcomes of the concerned random experiment. An alternative procedure is therefore suggested from frequentist viewpoint, involving relative credentials placed on the different candidate groups in terms of betting odds. The underlying theory was introduced in Chatterjee and Chattopadhyay(1993), the present study being an application towards the classification problem. Performance of the proposed rule has been studied for some real-life examples through discriminant analysis.

机译：分类问题涉及基于一些预先解决的案例，将关于几个变量的新观测值分配给已知存在先验的两个或多个不同类别。对于该问题，大多数现有解决方案都缺乏有关随机实验结果的详细推论。因此，从常客角度出发，提出了一种替代程序，其中涉及在投注赔率方面放置在不同候选人组上的相对证书。基本理论在Chatterjee和Chattopadhyay（1993）中得到了介绍，目前的研究是对分类问题的一种应用。通过判别分析，已针对某些实际示例研究了拟议规则的性能。

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来源
《International Triennial Calcutta Symposium on Probability and Statistics; 20031228-31; Calcutta(IN)》|2003年|P.283-294|共12页
会议地点 Calcutta(IN)
作者
Kaustav Banerjee;
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作者单位

St. Xavier's College, Kolkata, India;

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会议组织
原文格式 PDF
正文语种 eng
中图分类统计学;
关键词
classification problem; frequentist viewpoint;

机译：分类问题；频率论者观点;

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DETAILED CLASSIFICATION PROBLEM

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