Description Usage Arguments Value Examples
Calculates evaluation measures for a Petri nets and an Event Log
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 | 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()
|
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.
By default the |
convert |
|
variant |
The evaluation variant to be used. |
A list
with all available evaluation measures.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | if (pm4py_available()) {
library(eventdataR)
data(patients)
# As Inductive Miner of PM4PY is not life-cycle aware, keep only `complete` events:
patients_completes <- patients[patients$registration_type == "complete", ]
# Discover a Petri net
net <- discovery_inductive(patients_completes)
# Calculate evaluation measures for event log and Petri net
evaluation_all(patients_completes,
net$petrinet,
net$initial_marking,
net$final_marking)
}
|
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