Metric time series classification using weighted dynamic warping relative to centroids of classes
A. V. Goncharova, V. V. Strijovb
a Moscow Institute of Physics and Technology, 9 Institutskiy Per., Dolgoprudny, Moscow Region 141700, Russian Federation
b A. A. Dorodnicyn Computing Centre, Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, 40 Vavilov Str., Moscow 119333, Russian Federation
The paper discusses the problem of metric time series analysis and classification. The proposed classification model uses a matrix of distances between time series which is built with a fixed distance function. The dimension of this distance matrix is very high and all related calculations are time-consuming. The problem of reducing computational complexity is solved by selecting reference objects and using them for describing classes. The model that uses dynamic time warping for building reference objects or centroids is chosen as the basic model. This paper introduces a function of weights for each centroid that influences calculation of the distance measure. Time series of different analytic functions and time series of human activity from an accelerometer of a mobile phone are used as the objects for classification. The properties and the classification result of this model are investigated and compared with the properties of the basic model.
metric classification; weighted dynamic time warping; time series classification; centroid; distance function.
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A. V. Goncharov, V. V. Strijov, “Metric time series classification using weighted dynamic warping relative to centroids of classes”, Inform. Primen., 10:2 (2016), 36–47
Citation in format AMSBIB
\by A.~V.~Goncharov, V.~V.~Strijov
\paper Metric time series classification using weighted dynamic warping relative to centroids of classes
\jour Inform. Primen.
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