文章基本信息

标题：The k-NN algorithm for compositional data: a revised approach with and without zero values present
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作者：Michail Tsagris
期刊名称：Journal of Data Science
印刷版ISSN：1680-743X
电子版ISSN：1683-8602
出版年度：2014
卷号：12
期号：3
页码：519-534
出版社：Tingmao Publish Company
摘要：In compositional data, an observation is a vector with non-negative components which sum to a constant, typically 1. Data of this type arise in many areas, such as geology, archaeology, biology, economics and political science among others. The goal of this paper is to extend the taxicab metric and a newly suggested metric for com-positional data by employing a power transformation. Both metrics are to be used in the k-nearest neighbours algorithm regardless of the presence of zeros. Examples with real data are exhibited.
关键词：compositional data; entropy; k-NN algorithm; metric; supervised classification