Using dynamic time warping distances as features for improved time series classification

    Data Mining and Knowledge Discovery, Volume 30, Issue 2, 2015.

    Cited by: 83|Bibtex|Views19|Links
    EI
    Keywords:
    Time series classificationDynamic time warpingSymbolic aggregate approximation

    Abstract:

    Dynamic time warping (DTW) has proven itself to be an exceptionally strong distance measure for time series. DTW in combination with one-nearest neighbor, one of the simplest machine learning methods, has been difficult to convincingly outperform on the time series classification task. In this paper, we present a simple technique for time...More

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