sktime.transformations.panel.catch22_features

catch22 features A transformer for the catch22 features

class sktime.transformations.panel.catch22_features.Catch22[source]

Bases: sktime.transformations.base._PanelToTabularTransformer

Canonical Time-series Characteristics (catch22)

@article{lubba2019catch22,

title={catch22: CAnonical Time-series CHaracteristics}, author={Lubba, Carl H and Sethi, Sarab S and Knaute, Philip and

Schultz, Simon R and Fulcher, Ben D and Jones, Nick S},

journal={Data Mining and Knowledge Discovery}, volume={33}, number={6}, pages={1821–1852}, year={2019}, publisher={Springer}

}

Overview: Input n series length m Transforms series into the 22 catch22 features extracted from the hctsa toolbox.

Fulcher, B. D., & Jones, N. S. (2017). hctsa: A computational framework for automated time-series phenotyping using massive feature extraction. Cell systems, 5(5), 527-531.

Fulcher, B. D., Little, M. A., & Jones, N. S. (2013). Highly comparative time-series analysis: the empirical structure of time series and their methods. Journal of the Royal Society Interface, 10(83), 20130048.

catch22 package implementations: https://github.com/chlubba/catch22

For the Java version, see https://github.com/uea-machine-learning/tsml/blob/master/src/main/java /tsml/transformers/Catch22.java

transform(X, y=None)[source]

transforms data into the catch22 features

Parameters
  • X (pandas DataFrame, input time series) –

  • y (array_like, target values (optional, ignored)) –

Returns

Return type

Pandas dataframe containing 22 features for each input series