cluster_expectationMaximization: A class to perform Expectation-Maximization clustering on...
In pMineR: Processes Mining in Medicine

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)

1	cluster_expectationMaximization()

## 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)