FeatureUnion

class sktime.series_as_features.compose.FeatureUnion(transformer_list, n_jobs=None, transformer_weights=None, preserve_dataframe=True)[source]

Concatenates results of multiple transformer objects. This estimator applies a list of transformer objects in parallel to the input data, then concatenates the results. This is useful to combine several feature extraction mechanisms into a single transformer. Parameters of the transformations may be set using its name and the parameter name separated by a ‘__’. A transformer may be replaced entirely by setting the parameter with its name to another transformer, or removed by setting to ‘drop’ or None. :param transformer_list: List of transformer objects to be applied to the data. The first

half of each tuple is the name of the transformer.

Parameters
  • n_jobs (int or None, optional (default=None)) – Number of jobs to run in parallel. None means 1 unless in a joblib.parallel_backend context. -1 means using all processors.

  • transformer_weights (dict, optional) – Multiplicative weights for features per transformer. Keys are transformer names, values the weights.

__init__(transformer_list, n_jobs=None, transformer_weights=None, preserve_dataframe=True)[source]

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