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A local mean-based nonparametric classifier

机译:基于局部均值的非参数分类器

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摘要

A considerable amount of effort has been devoted to design a classifier in practical situations. In this paper, a simple nonparametric classifier based on the local mean vectors is proposed. The proposed classifier is compared with the 1-NN, k-NN, Euclidean distance (ED), Parzen, and artificial neural network (ANN) classifiers in terms of the error rate on the unknown patterns, particularly in small training sample size situations. Experimental results show that the proposed classifier is promising even in practical situations.
机译:在实际情况下,已经投入了大量的精力来设计分类器。本文提出了一种基于局部均值向量的简单非参数分类器。根据未知模式的错误率,将拟议的分类器与1-NN,k-NN,欧氏距离(ED),Parzen和人工神经网络(ANN)分类器进行比较,尤其是在训练样本量较小的情况下。实验结果表明,提出的分类器即使在实际情况下也很有希望。

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