pm4py.algo.clustering.trace_attribute_driven.algorithm module#

class pm4py.algo.clustering.trace_attribute_driven.algorithm.Variants(*values)[source]#

Bases: Enum

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 '/Users/chris/Desktop/PIS/pm4py2/pm4py/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: EventLog | EventStream | DataFrame, trace_attribute: str, variant=<function eval_DMM_leven>, parameters: Any, ~typing.Any] | None=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