evaluation: Calculates evaluation measures for a Petri nets and an Event...
In fmannhardt/pm4py: Interface to the 'PM4py' Process Mining Library

evaluation

R Documentation

Calculates evaluation measures for a Petri nets and an Event Log

Description

Calculates evaluation measures for a Petri nets and an Event Log

Usage

evaluation_all(
  eventlog,
  petrinet,
  initial_marking,
  final_marking,
  parameters = default_parameters(eventlog),
  convert = TRUE
)

evaluation_precision(
  eventlog,
  petrinet,
  initial_marking,
  final_marking,
  parameters = default_parameters(eventlog),
  variant = variant_precision_etconformance(),
  convert = TRUE
)

variant_precision_etconformance()

evaluation_fitness(
  eventlog,
  petrinet,
  initial_marking,
  final_marking,
  parameters = default_parameters(eventlog),
  variant = variant_fitness_token_based(),
  convert = TRUE
)

variant_fitness_token_based()

variant_fitness_alignment_based()

Arguments

`eventlog`	A bupaR or PM4PY event log.
`petrinet`	A bupaR or PM4PY Petri net.
`initial_marking`	A R vector with the place identifiers of the initial marking or a PM4PY marking. By default the initial marking of the bupaR Petri net will be used if available.
`final_marking`	A R vector with the place identifiers of the final marking or a PM4PY marking.
`parameters`	PM4PY alignment parameter.
`convert`	`TRUE` to automatically convert Python objects to their R equivalent. If you pass `FALSE` you can do manual conversion using the r-py-conversion function.
`variant`	Variant used By default the `activity_key` from the bupaR event log is specified using param_activity_key.