pm4py.algo.transformation.trace_encodings.variants.one_hot module#

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class pm4py.algo.transformation.trace_encodings.variants.one_hot.Parameters(*values)[source]#

Bases: Enum

EVENT_ATTRIBUTES = 'event_attributes'#
TRACE_ATTRIBUTES = 'trace_attributes'#
RETURN_SPARSE = 'return_sparse'#
VECTORIZER = 'vectorizer'#
FIT_VECTORIZER = 'fit_vectorizer'#
pm4py.algo.transformation.trace_encodings.variants.one_hot.apply(log: EventLog | EventStream | DataFrame, parameters: Dict[Any, Any] | None = None)[source]#

Encodes each trace as a binary vector of present trace tokens.

Parameters:

  • log – Event log, event stream, or dataframe containing traces.

  • parameters – Parameters of the encoding. Common options: - EVENT_ATTRIBUTES: event attributes used to form tokens. Defaults to

    the activity attribute.

    • TRACE_ATTRIBUTES: case attributes added as context tokens.

    • RETURN_SPARSE: if True, returns the sklearn sparse matrix.

Returns:

  • data – One row per trace, one binary value per discovered token.

  • feature_names – Token names corresponding to the columns of data.