/** * Constructor. Sets defaults for each member variable. Default Clusterer is * EM. */ public ClusterEvaluation() { setClusterer(new SimpleKMeans()); m_clusteringResults = new StringBuffer(); m_clusterAssignments = null; }
/** * Constructor. Sets defaults for each member variable. Default Clusterer is * EM. */ public ClusterEvaluation() { setClusterer(new SimpleKMeans()); m_clusteringResults = new StringBuffer(); m_clusterAssignments = null; }
eval.setClusterer(clusterer); try { eval.evaluateClusterer(train);
m_clusterer.buildClusterer(train); double numClusters = m_clusterer.numberOfClusters(); eval.setClusterer(m_clusterer); long trainTimeElapsed = System.currentTimeMillis() - trainTimeStart; long testTimeStart = System.currentTimeMillis();
m_clusterer.buildClusterer(train); double numClusters = m_clusterer.numberOfClusters(); eval.setClusterer(m_clusterer); long trainTimeElapsed = System.currentTimeMillis() - trainTimeStart; long testTimeStart = System.currentTimeMillis();
Instances instances = new Instances("iris.arff"); SimpleKMeans simpleKMeans = new SimpleKMeans(); // build clusterer simpleKMeans.setPreservationOrder(true); simpleKMeans.setNumClusters(2); simpleKMeans.buildClusterer(instances); ClusterEvaluation eval = new ClusterEvaluation(); eval.setClusterer(simpleKMeans); eval.evaluateClusterer(instances); System.out.println("Cluster Evaluation: "+eval.clusterResultsToString());
ce.setClusterer(clusterer); ce.evaluateClusterer(train, trainFileName);
eval.setClusterer(clusterer);
eval.setClusterer(clusterer);
eval.setClusterer(clusterer); switch (testMode) { case 3:
m_eval.setClusterer(m_clusterer);
eval.setClusterer(clusterer); eval.setClusterer(clusterer); try { eval.evaluateClusterer(testData);
eval.setClusterer(clusterer); eval.setClusterer(clusterer); try { eval.evaluateClusterer(testData);
m_eval.setClusterer(m_clusterer);
evaluationI = new ClusterEvaluation(); clusterers[0].buildClusterer(train); evaluationB.setClusterer(clusterers[0]); evaluationB.evaluateClusterer(train); } catch (Exception ex) { evaluationI.setClusterer(clusterers[1]); evaluationI.evaluateClusterer(train); if (evaluationB.equals(evaluationI)) {
evaluationI = new ClusterEvaluation(); clusterers[0].buildClusterer(train); evaluationB.setClusterer(clusterers[0]); evaluationB.evaluateClusterer(train); } catch (Exception ex) { evaluationI.setClusterer(clusterers[1]); evaluationI.evaluateClusterer(train); if (evaluationB.equals(evaluationI)) {
clusterer.buildClusterer(train1); built = true; evaluation1A.setClusterer(clusterer); evaluation1A.evaluateClusterer(train1); clusterer.buildClusterer(train2); built = true; evaluation2.setClusterer(clusterer); evaluation2.evaluateClusterer(train2); clusterer.buildClusterer(train1); built = true; evaluation1B.setClusterer(clusterer); evaluation1B.evaluateClusterer(train1);
evaluationI = new ClusterEvaluation(); clusterers[0].buildClusterer(train); evaluationB.setClusterer(clusterers[0]); evaluationB.evaluateClusterer(train); } catch (Exception ex) { evaluationI.setClusterer(clusterers[1]); evaluationI.evaluateClusterer(train); if (!evaluationB.equals(evaluationI)) {
clusterer.buildClusterer(train1); built = true; evaluation1A.setClusterer(clusterer); evaluation1A.evaluateClusterer(train1); clusterer.buildClusterer(train2); built = true; evaluation2.setClusterer(clusterer); evaluation2.evaluateClusterer(train2); clusterer.buildClusterer(train1); built = true; evaluation1B.setClusterer(clusterer); evaluation1B.evaluateClusterer(train1);
evaluationI = new ClusterEvaluation(); clusterers[0].buildClusterer(train); evaluationB.setClusterer(clusterers[0]); evaluationB.evaluateClusterer(train); } catch (Exception ex) { evaluationI.setClusterer(clusterers[1]); evaluationI.evaluateClusterer(train); if (!evaluationB.equals(evaluationI)) {