edeaR (version 0.8.6)

activity_presence: Metric: Activity Presence

Description

Calculates for each activity type in what percentage of cases it is present.

Usage

activity_presence(eventlog, append, append_column, sort, ...)
# S3 method for eventlog
activity_presence(
  eventlog,
  append = F,
  append_column = "absolute",
  sort = TRUE,
  ...
)
# S3 method for grouped_eventlog
activity_presence(
  eventlog,
  append = F,
  append_column = "absolute",
  sort = TRUE,
  ...
)

Arguments

eventlog

The dataset to be used. Should be a (grouped) eventlog object. eventlog.

append

Logical, indicating whether to append results to original event log. Ignored when level is log or trace.

append_column

Which of the output columns to append to log, if append = T. Default column depends on chosen level.

sort

Sort output on count. Defaults to TRUE. Only for levels with frequency count output.

...

Deprecated arguments

Methods (by class)

• eventlog: Compute activity presence for event log

• grouped_eventlog: Compute activity presence for grouped eventlog

Details

An indication of variance can be the presence of the activities in the different cases. This metric shows for each activity the absolute number of cases in which each activity occurs together with its relative presence.

References

Swennen, M. (2018). Using Event Log Knowledge to Support Operational Exellence Techniques (Doctoral dissertation). Hasselt University.

Examples

if (FALSE) {
data <- data.frame(case = rep("A",5),
activity_id = c("A","B","C","D","E"),
activity_instance_id = 1:5,
lifecycle_id = rep("complete",5),
timestamp = 1:5,
resource = rep("resource 1", 5))

log <- bupaR::eventlog(data,case_id = "case",
activity_id = "activity_id",
activity_instance_id = "activity_instance_id",
lifecycle_id = "lifecycle_id",
timestamp = "timestamp",
resource_id = "resource")

activity_presence(log)
}