Computer Science ›› 2016, Vol. 43 ›› Issue (5): 257-260.doi: 10.11896/j.issn.1002-137X.2016.05.048

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Incremental Time Series Classification Algorithm Based on Shapelets

DING Jian and WANG Shu-ying   

  • Online:2018-12-01 Published:2018-12-01

Abstract: This paper focused on research of time series classification according to time series features of high dimensionality,ordered real-valued variables,autocorrelation and so on.From the perspective of image processing,this paper proposed a method for ITTS to transform image information to time series.As the best approach to show a subsequence of time series,shapelets would change dynamically as time goes on.Considering this thought,this paper presented time series classification algorithm based on dynamically finding shapelets which is named IPST algorithm.IPST algorithm dynamically discoveries current optimal k shapelets well,so as to improve the accuracy of time series classification.The discovered shapelets can be also used with state-of-art classification algorithms,leading to better performance.

Key words: Time series,Classification,Shapelets,Image processing,Incremental learning

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