摘要： 贝叶斯分类器、最小距离分类器、近邻分类器和BP网络等是比较常用的分类器，为提高这些分类器的性能，引入了Box-Cox变换的思想。将Box-Cox变换用于数据正态化处理技术，并对常用分类器的性能进行改进。实验结果显示，通过引入Box-Cox变换，分类器的分类正确率有较大的提高。

关键词: Box-Cox变换, 贝叶斯分类器, 近邻分类器, 最小距离分类器, BP神经网络

Abstract: Bayes classifier, minimum distance classifier, nearest neighbour classifier and back propagation neural networks are widely used classifiers. In order to improve their performance, this paper introduces the idea of Box-Cox transformation. Box-Cox transformation, which can transform the data and make the distribution nearer normal distribution, is a simple but quite effective data processing technology. Experiment results show that, as the result of the introducation of Box-Cox transformation, the accurate rate of classifiers is improved remarkably.

Key words: Box-Cox transformation, Bayes classifier, nearest neighbour classifier, minimum distance classifier, BP neural network

中图分类号: 

• TP18