precision_alignments: Apply the *precision* alignments algorithm between a log and...

In fmannhardt/pm4py: Interface to the 'PM4py' Process Mining Library

Apply the precision alignments algorithm between a log and a process model

Description

Calculates the precision of the model w.r.t. the event log using alignments.

Usage

precision_alignments(
  log,
  marked_petrinet,
  multi_processing = FALSE,
  convert = TRUE
)

Arguments

log	log: Object of class log or derivatives (grouped_log, eventlog,
marked_petrinet	A Marked Petrinet as defined by petrinetR, e.g. the output of discover_inductive or discover_alpha.
multi_processing	logical (default FALSE): Disables if FALSE, enables if TRUE multiprocessing in inductive miner.
convert	logical (default: TRUE): 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.

Value

precision metric.

Examples

## Not run: 
library(pm4py)
library(eventdataR)

model <- discover_alpha(patients)
precision_alignments(patients, model)


## End(Not run)

fmannhardt/pm4py documentation built on July 21, 2023, 10:55 p.m.