pm4py.algo.clustering.trace_attribute_driven 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/>.

Subpackages#

Submodules#

pm4py.algo.clustering.trace_attribute_driven.algorithm 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.trace_attribute_driven.algorithm.Variants(value)[source]#

Bases: Enum

An enumeration.

VARIANT_DMM_LEVEN(percent, alpha)#
VARIANT_AVG_LEVEN(percent, alpha)#
VARIANT_DMM_VEC(percent, alpha)#
VARIANT_AVG_VEC(percent, alpha)#
DFG = <module 'pm4py.algo.clustering.trace_attribute_driven.dfg.dfg_dist' from 'C:\\Users\\berti\\pm4py-core\\pm4py\\algo\\clustering\\trace_attribute_driven\\dfg\\dfg_dist.py'>#
pm4py.algo.clustering.trace_attribute_driven.algorithm.bfs(tree)[source]#
pm4py.algo.clustering.trace_attribute_driven.algorithm.apply(log: ~typing.Union[~pm4py.objects.log.obj.EventLog, ~pm4py.objects.log.obj.EventStream, ~pandas.core.frame.DataFrame], trace_attribute: str, variant=<function eval_DMM_leven>, parameters: ~typing.Optional[~typing.Dict[~typing.Any, ~typing.Any]] = None) Any[source]#

Apply the hierarchical clustering to a log starting from a trace attribute.

MSc Thesis is available at: https://www.pads.rwth-aachen.de/global/show_document.asp?id=aaaaaaaaalpxgft&download=1 Defense slides are available at: https://www.pads.rwth-aachen.de/global/show_document.asp?id=aaaaaaaaalpxgqx&download=1

Parameters#

log

Log

trace_attribute

Trace attribute to exploit for the clustering

variant

Variant of the algorithm to apply, possible values: - Variants.VARIANT_DMM_LEVEN (that is the default) - Variants.VARIANT_AVG_LEVEN - Variants.VARIANT_DMM_VEC - Variants.VARIANT_AVG_VEC - Variants.DFG

Returns#

tree

Hierarchical cluster tree

leafname

Root node