tsfresh.convenience package


tsfresh.convenience.relevant_extraction module

tsfresh.convenience.relevant_extraction.extract_relevant_features(timeseries_container, y, X=None, feature_extraction_settings=None, feature_selection_settings=None, column_id=None, column_sort=None, column_kind=None, column_value=None)[source]

High level convenience function to extract time series features from timeseries_container. Then return feature matrix X possibly augmented with features relevant with respect to target vector y.

For more details see the documentation of extract_features() and select_features().


>>> from tsfresh.examples import load_robot_execution_failures
>>> from tsfresh import extract_relevant_features
>>> df, y = load_robot_execution_failures()
>>> X = extract_relevant_features(df, y, column_id='id', column_sort='time')

Feature matrix X, possibly extended with relevant time series features.

Module contents

The convenience submodule contains methods that allow the user to extract and filter features conveniently.