Abstract
Time series shapelets are a recent promising concept in time series data mining. Shapelets are time series snippets that can be used to classify unlabeled time series. Although shapelets are a useful concept, the current literature illustrates the fact that shapelet discovery is a time-consuming task. In this paper, we propose a fast shapelets discovery algorithm that outperforms the current algorithm; our experimental results demonstrate that the classification accuracy of the proposed algorithm is not significantly different from the accuracy obtained by the current algorithms, but the running time scalability is better.
Retraction of this chapter can be found at DOI 10.1007/978-3-662-45969-0_37.
An erratum to this chapter can be found at http://dx.doi.org/10.1007/978-3-662-45969-0_37
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References
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Zhang, Z. (2015). Retracted: A Fast Time Series Shapelets Data Mining Algorithm. In: Feng, S., Huang, W., Wang, J., Wang, M., Zha, J. (eds) Low-carbon City and New-type Urbanization. Environmental Science and Engineering(). Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45969-0_32
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DOI: https://doi.org/10.1007/978-3-662-45969-0_32
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