On Kleinberg's Stochastic Discrimination Procedure

Irle Albrecht; Kauschke Jonas

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On Kleinberg's Stochastic Discrimination Procedure

机译：克莱因伯格的随机歧视程序

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摘要

A new condition for high accuracy on test sets is given for the method of stochastic discrimination (SD), a pattern recognition method introduced by Kleinberg. This condition provides a simple explanation for the observed good generalization properties and overtraining-resistance. We also show that the method of SD remains valid if the original assumption of uniform distribution on a finite space for resampling is relaxed.

机译：随机判别法（SD）是由Kleinberg引入的一种模式识别方法，为测试集的高精度提供了新条件。此条件为观察到的良好泛化特性和抗过度训练性提供了简单的解释。我们还表明，如果放宽了有限空间上用于重采样的均匀分布的原始假设，则SD方法仍然有效。

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《Pattern Analysis and Machine Intelligence, IEEE Transactions on》 |2011年第7期|p.1482-1486|共5页
作者
Irle Albrecht; Kauschke Jonas;
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作者单位

University of Kiel, Kiel;

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正文语种 eng
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Pattern recognition; stochastic discrimination.;

机译：模式识别;随机歧视。;

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3. Stochastically Ordered Subpopulations and Optimal Burn-In Procedure [J] . Cha J. H., Finkelstein M. Reliability, IEEE Transactions on . 2010,第4期

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On Kleinberg's Stochastic Discrimination Procedure

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