wildboar.transform._rocket#

Module Contents#

Classes#

RocketTransform

Transform a time series using random convolution features
class wildboar.transform._rocket.RocketTransform(n_kernels=1000, *, sampling='normal', sampling_params=None, kernel_size=None, bias_prob=1.0, normalize_prob=1.0, padding_prob=0.5, n_jobs=None, random_state=None)[source]#

Bases: wildboar.transform.base.BaseFeatureEngineerTransform

Transform a time series using random convolution features

embedding_[source]#

The underlying embedding

Type:

Embedding

References

Dempster, Angus, François Petitjean, and Geoffrey I. Webb.

ROCKET: exceptionally fast and accurate time series classification using random convolutional kernels. Data Mining and Knowledge Discovery 34.5 (2020): 1454-1495.

Parameters:

  • n_kernels (int, optional) – The number of kernels.

  • n_jobs (int, optional) – The number of jobs to run in parallel. None means 1 and -1 means using all processors.

  • random_state (int or RandomState, optional) – The psuodo-random number generator.