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Selecting Optimal Trace Clustering Pipelines with AutoML
[article]
2021
arXiv
pre-print
Trace clustering has been extensively used to preprocess event logs. By grouping similar behavior, these techniques guide the identification of sub-logs, producing more understandable models and conformance analytics. Nevertheless, little attention has been posed to the relationship between event log properties and clustering quality. In this work, we propose an Automatic Machine Learning (AutoML) framework to recommend the most suitable pipeline for trace clustering given an event log, which
arXiv:2109.00635v1
fatcat:jvvqi7wbqjggnbebjjrtzkmory