@operator(
value = {"clustering_em"},
content_type = IType.LIST,
category = {IOperatorCategory.STATISTICAL},
concept = {IConcept.STATISTIC})
@doc(
value =
"A list of agent groups clustered by EM Algorithm based on the given attributes. Some paremeters can be defined: "
+ "max_iterations: the maximum number of iterations to perform;"
+ "num_clusters: the number of clusters; minStdDev: minimum allowable standard deviation",
examples = {
@example(
value =
"clustering_em([ag1, ag2, ag3, ag4, ag5],[\"size\",\"age\", \"weight\"],[\"max_iterations\"::10, \"num_clusters\"::3])",
equals = "for example, can return [[ag1, ag3], [ag2], [ag4, ag5]]",
isExecutable = false)
},
see = {
"clustering_xmeans",
"clustering_simple_kmeans",
"clustering_farthestFirst",
"clustering_DBScan",
"clustering_cobweb"
})
public static IList<IList<IAgent>> primClusteringEM(
final IScope scope,
final IAddressableContainer<Integer, IAgent, Integer, IAgent> agents,
final IList<String> attributes,
final GamaMap<String, Object> parameters) {
EM em = new EM();
em.setSeed(Cast.asInt(scope, scope.getRandom().getSeed()));
if (parameters != null) {
try {
if (parameters.containsKey("max_iterations")) {
em.setMaxIterations(Cast.asInt(scope, parameters.get("max_iterations")));
}
if (parameters.containsKey("num_clusters")) {
em.setNumClusters(Cast.asInt(scope, parameters.get("num_clusters")));
}
if (parameters.containsKey("minStdDev")) {
em.setMinStdDev(Cast.asFloat(scope, parameters.get("minStdDev")));
}
} catch (Exception e) {
}
}
IList<IList<IAgent>> groupes = clusteringUsingWeka(scope, em, attributes, agents);
return groupes;
}