This paper presents a command-line tool, called Entropia, that implements a family of conformance checking measures for process mining founded on the notion of entropy from information theory. The measures allow quantifying classical non-deterministic and stochastic precision and recall quality criteria for process models automatically discovered from traces executed by IT-systems and recorded in their event logs. A process model has good precision with respect to the log it was discovered from if it does not encode many traces that are not part of the log, and has good recall if it encodes most of the traces from the log. By definition, the measures possess useful properties and can often be computed quickly.
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