/** Builds the clusters */
private void buildClusterer() throws Exception {
if (m_trainingSet.classIndex() < 0) m_Clusterer.buildClusterer(m_trainingSet);
else { // class based evaluation if class attribute is set
Remove removeClass = new Remove();
removeClass.setAttributeIndices("" + (m_trainingSet.classIndex() + 1));
removeClass.setInvertSelection(false);
removeClass.setInputFormat(m_trainingSet);
Instances clusterTrain = Filter.useFilter(m_trainingSet, removeClass);
m_Clusterer.buildClusterer(clusterTrain);
}
}
private static IList<IList<IAgent>> clusteringUsingWeka(
final IScope scope,
final Clusterer clusterer,
final IList<String> attributes,
final IAddressableContainer<Integer, IAgent, Integer, IAgent> agents)
throws GamaRuntimeException {
Instances dataset = convertToInstances(scope, attributes, agents);
try {
clusterer.buildClusterer(dataset);
IList<IList<IAgent>> groupes = GamaListFactory.create(Types.LIST.of(Types.AGENT));
for (int i = 0; i < clusterer.numberOfClusters(); i++) {
groupes.add(GamaListFactory.<IAgent>create(Types.AGENT));
}
for (int i = 0; i < dataset.numInstances(); i++) {
Instance inst = dataset.instance(i);
int clusterIndex = -1;
clusterIndex = clusterer.clusterInstance(inst);
IList<IAgent> groupe = groupes.get(clusterIndex);
groupe.add(agents.get(scope, i));
}
return groupes;
} catch (Exception e) {
return null;
}
}
