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JOURNALS // Sistemy i Sredstva Informatiki [Systems and Means of Informatics] // Archive

Sistemy i Sredstva Inform., 2015 Volume 25, Issue 4, Pages 52–64 (Mi ssi433)

This article is cited in 2 papers

Metric time series classification using dynamic warping relative to centroids of classes

A. V. Goncharova, M. S. Popovaa, V. V. Strijovb

a Moscow Institute of Physics and Technology, 9 Institutskiy Per., Dolgoprudny, Moscow Region 141700, Russian Federation
b Dorodnicyn Computing Center, Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences, 40 Vavilov Str., Moscow 119333, Russian Federation

Abstract: The paper discusses the problem of time series classification in the case of several classes. The proposed classification model uses the matrix of distance between time series. This distance measure is defined by the dynamic time warping method. The dimension of the distance matrix is very high. The paper introduces centroids of each class as reference objects used to decrease this dimension. The distance matrix with lower dimension describes the distance between all objects and reference objects. This method is used for human activity recognition. The quality of classification on data from a mobile accelerometer is investigated. This metric algorithm of classification is compared with the separating classification algorithm.

Keywords: metric classification; dynamic time warping; time series classification; centroid; distance function.

Received: 16.07.2015

DOI: 10.14357/08696527150404



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