An Altered Kernel Transformation for Time Series Classification

@inproceedings{Xue2017AnAK,
  title={An Altered Kernel Transformation for Time Series Classification},
  author={Yangtao Xue and Li Zhang and Zhiwei Tao and Bangjun Wang and Fanzhang Li},
  booktitle={ICONIP},
  year={2017}
}
Motivated by the great efficiency of dynamic time warping (DTW) for time series similarity measure, a Gaussian DTW (GDTW) kernel has been developed for time series classification. This paper proposes an altered Gaussian DTW (AGDTW) kernel function, which takes into consideration each of warping path between time series. Time series can be mapped into a special kernel space where the homogeneous data gather together and the heterogeneous data separate from each other. Classification results on… CONTINUE READING

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