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http://dx.doi.org/10.7465/jkdi.2016.27.3.621

Categorical time series clustering: Case study of Korean pro-baseball data  

Pak, Ro Jin (Department of Applied Statistics, Dankook University)
Publication Information
Journal of the Korean Data and Information Science Society / v.27, no.3, 2016 , pp. 621-627 More about this Journal
Abstract
A certain professional baseball team tends to be very weak against another particular team. For example, S team, the strongest team in Korea, is relatively weak to H team. In this paper, we carried out clustering the Korean baseball teams based on the records against the team S to investigate whether the pattern of the record of the team H is different from those of the other teams. The technique we have employed is 'time series clustering', or more specifically 'categorical time series clustering'. Three methods have been considered in this paper: (i) distance based method, (ii) genetic sequencing method and (iii) periodogram method. Each method has its own advantages and disadvantages to handle categorical time series, so that it is recommended to draw conclusion by considering the results from the above three methods altogether in a comprehensive manner.
Keywords
Categorical time series; evolutionary tree; frequency analysis; periodogram; spectral analysis;
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Times Cited By KSCI : 7  (Citation Analysis)
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