pMineR (version 0.31)

cluster_expectationMaximization: A class to perform Expectation-Maximization clustering on sequential data for Process Mining issues

Description

This class performs sequence clustering on an event-log with the Expectation-Maximization (EM) algorithm. The public methods are:

• cluster_expectationMaximization( ) is the constructor of the class
• loadDataset( ) loads data taken from a dataLoader::getData() method, into a cluster_expectationMaximization() object
• calculateClusters( ) performs the actual clustering computation on the previously loaded dataset
• getClusters( ) returns the clusters computed by the cluster_expectationMaximization::calculateClusters() method
• getClusterStats( ) returns informations about the clustering result (i.e. support, between-cluster distance, within-cluster mean distance and standard deviation)
• getClusterLog( ) returns informations about the clustering computation itself (i.e. iterations needed to converge, centroids value after each iteration)

In order to better undestand the use of such methods, please visit: www.pminer.info Parameters for cluster_expectationMaximization::calculateClusters() method are:

• num the number of clusters it has to generate
• typeOfModel the name of the Process Mining model it has to use to generate the space (up to now, only the default "firstOrdermarkovModel" is provided)

Usage

cluster_expectationMaximization()

Examples

## Not run: 
# 
# # create a Loader
# 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$load.csv(nomeFile = "./otherFiles/test_02.csv",
# IDName = "ID",EVENTName = "DES", dateColumnName = "DATA")
# 
# # now create an object cluster_expectationMaximization
# obj.clEM<- cluster_expectationMaximization();
# 
# # load the data into logInspector object
# obj.clEM$loadDataset( obj.L$getData() );
# 
# # perform clustering computation
# obj.clEM$calculateClusters(num = 5, typeOfModel = "firstOrderMarkovModel");
# 
# # get calculated clusters 
# a <- obj.clEM$getClusters();
# 
# # get informations about performance of clusters
# b <- obj.clEM$getClusterStats();
# 
# # get log of each iteration of the algorithm
# d <- obj.clEM$getClusterLog();
# ## End(Not run)