logInspector: A class to perform a preliminary analysis on sequential data...

In pMineR: Processes Mining in Medicine

Description

This class aims at inspecting an event-log for descriptive analysis purposes. The public methods are:

• logInspector( ) is the constructor of the class

• loadDataset( ) loads data taken from a dataLoader::getData() method, into a logInspector() object

• getEventStats() computes and returns event-related stats, such as absolute and relative events frequency

• getProcessStats() computes and returns process-related stats, such as absolute and relative processes frequency

• plotEventStats( ) plots the event-related stats (input is the number of most frequent events it has to plot)

• plotProcessStats( ) plots the process-related stats (input is the number of most frequent processes it has to plot)

• timeDistribution.stats.plot( ) <not yet commented>

In order to better undestand the use of such methods, please visit: www.pminer.info

Parameter for logInspector::plotEventStats() and logInspector::plotProcessStats() methods is:

• num the number of most frequent events/processes to plot

Usage

logInspector()

Examples

## Not run: 
# -----------------------------------------------
#  USING THE METHODS of the class
# -----------------------------------------------
obj.L<-dataLoader();   # create a Loader

# Load a .csv using "DES" and "ID" as column names to indicate events
# and Patient's ID
obj.L$load.csv(nomeFile = "../otherFiles/test_02.csv",
IDName = "ID",EVENTName = "DES",dateColumnName = "DATA")

# now create an object logInspector
obj.logI<-logInspector();

# load the data into logInspector object
obj.logI$loadDataset( obj.L$getData() );

# get event-related descriptive statistics
obj.logI$getEventStats();

# get process-related descriptive statistics
obj.logI$getProcessStats();

# plot event-related descriptive statistics
obj.logI$plotEventStats();

# plot process-related descriptive statistics
obj.logI$plotProcessStats()

## End(Not run)

pMineR documentation built on May 2, 2019, 9:34 a.m.