Systems and Means of Informatics
2015, Volume 25, Issue 4, pp 52-64
METRIC TIME SERIES CLASSIFICATION USING DYNAMIC WARPING RELATIVE TO CENTROIDS OF CLASSES
- A. V. Goncharov
- M. S. Popova
- V. V. Strijov
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.
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[+] About this article
Title
METRIC TIME SERIES CLASSIFICATION USING DYNAMIC WARPING RELATIVE TO CENTROIDS OF CLASSES
Journal
Systems and Means of Informatics
Volume 25, Issue 4, pp 52-64
Cover Date
2015-09-30
DOI
10.14357/08696527150404
Print ISSN
0869-6527
Publisher
Institute of Informatics Problems, Russian Academy of Sciences
Additional Links
Key words
metric classification; dynamic time warping; time series classification; centroid; distance function
Authors
A. V. Goncharov  , M. S. Popova ,
and V. V. Strijov 
Author Affiliations
Moscow Institute of Physics and Technology, 9 Institutskiy Per., Dolgoprudny, Moscow Region 141700, Russian Federation
Dorodnicyn Computing Center, Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences, 40 Vavilov Str., Moscow 119333, Russian Federation
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