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The K-NN Algorithm for Compositional Data: A Revised Approach with and without Zero Values Present
Volume 12, Issue 3 (2014), pp. 519–534
Michail Tsagris  

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https://doi.org/10.6339/JDS.201407_12(3).0008
Pub. online: 4 August 2022      Type: Research Article      Open accessOpen Access

Published
4 August 2022

Abstract

Abstract: 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.

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Keywords
compositional data entropy k-NN algorithm

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