pm4py.algo.clustering.profiles.variants package#

This file is part of PM4Py (More Info: https://pm4py.fit.fraunhofer.de).

PM4Py is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

PM4Py is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with PM4Py. If not, see <https://www.gnu.org/licenses/>.

Submodules#

pm4py.algo.clustering.profiles.variants.sklearn_profiles module#

This file is part of PM4Py (More Info: https://pm4py.fit.fraunhofer.de).

PM4Py is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

PM4Py is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with PM4Py. If not, see <https://www.gnu.org/licenses/>.

class pm4py.algo.clustering.profiles.variants.sklearn_profiles.Parameters(value)[source]#

Bases: Enum

An enumeration.

SKLEARN_CLUSTERER = 'sklearn_clusterer'#
pm4py.algo.clustering.profiles.variants.sklearn_profiles.apply(log: Union[EventLog, EventStream, DataFrame], parameters: Optional[Dict[Any, Any]] = None) Generator[EventLog, None, None][source]#

Cluster the event log, based on the extraction of profiles for the traces of the event log (by means of the feature extraction proposed in pm4py) and the application of a Scikit learn clusterer (default: K-means with two clusters)

Implements the approach described in: Song, Minseok, Christian W. Günther, and Wil MP Van der Aalst. “Trace clustering in process mining.” Business Process Management Workshops: BPM 2008 International Workshops, Milano, Italy, September 1-4, 2008. Revised Papers 6. Springer Berlin Heidelberg, 2009.

Parameters#

log

Event log

parameters

Parameters of the feature extraction, including: - Parameters.SKLEARN_CLUSTERER => the Scikit-Learn clusterer to be used (default: KMeans(n_clusters=2, random_state=0, n_init=”auto”))

Returns#

generator

Generator of logs (clusters)