Rocket

class sktime.transformations.panel.rocket.Rocket(num_kernels=10000, normalise=True, random_state=None)[source]

ROCKET

RandOm Convolutional KErnel Transform

@article{dempster_etal_2019,

author = {Dempster, Angus and Petitjean, Francois and Webb, Geoffrey I}, title = {ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernels}, year = {2019}, journal = {arXiv:1910.13051}

}

Parameters
  • num_kernels (int, number of random convolutional kernels (default 10,000)) –

  • normalise (boolean, whether or not to normalise the input time) –

  • per instance (default True) (series) –

  • random_state (int (ignored unless int due to compatability with Numba),) –

  • seed (optional (random) –

  • None) (default) –

__init__(num_kernels=10000, normalise=True, random_state=None)[source]

Initialize self. See help(type(self)) for accurate signature.