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());
outBuff.append(eval.clusterResultsToString()); outBuff.append("\n"); m_History.updateResult(name);
outBuff.append(eval.clusterResultsToString()); outBuff.append("\n"); m_History.updateResult(name);
throw new Exception("Test mode not implemented"); outBuff.append(eval.clusterResultsToString()); outBuff.append("\n"); m_History.updateResult(name);
throw new Exception("Test mode not implemented"); outBuff.append(eval.clusterResultsToString()); outBuff.append("\n"); m_History.updateResult(name);
+ " instances ===\n\n" + "Scheme: " + textTitle + "\n" + "Relation: " + ce.getTestSet().getDataSet().relationName() + "\n\n" + m_eval.clusterResultsToString(); if (numericClass) { resultT = resultT
String resultT = "=== Evaluation result for training instances ===\n\n" + "Scheme: " + clusterSpec + "\n" + "Relation: " + trainData.relationName() + "\n\n" + eval.clusterResultsToString(); String resultT = "=== Evaluation result for test instances ===\n\n" + "Scheme: " + clusterSpec + "\n" + "Relation: " + testData.relationName() + "\n\n" + eval.clusterResultsToString(); if (testData.classIndex() >= 0 && testData.classAttribute().isNumeric()) {
String resultT = "=== Evaluation result for training instances ===\n\n" + "Scheme: " + clusterSpec + "\n" + "Relation: " + trainData.relationName() + "\n\n" + eval.clusterResultsToString(); String resultT = "=== Evaluation result for test instances ===\n\n" + "Scheme: " + clusterSpec + "\n" + "Relation: " + testData.relationName() + "\n\n" + eval.clusterResultsToString(); if (testData.classIndex() >= 0 && testData.classAttribute().isNumeric()) {
+ " instances ===\n\n" + "Scheme: " + textTitle + "\n" + "Relation: " + ce.getTestSet().getDataSet().relationName() + "\n\n" + m_eval.clusterResultsToString(); if (numericClass) { resultT = resultT
println("Here are the results:\n"); println("\nbatch built results\n" + evaluationB.clusterResultsToString()); println("\nincrementally built results\n" + evaluationI.clusterResultsToString()); println("Here are the datasets:\n"); println("=== Train Dataset ===\n" + train.toString() + "\n");
println("Here are the results:\n"); println("\nbatch built results\n" + evaluationB.clusterResultsToString()); println("\nincrementally built results\n" + evaluationI.clusterResultsToString()); println("Here are the datasets:\n"); println("=== Train Dataset ===\n" + train.toString() + "\n");
println("Here are the results:\n"); println("\nboth methods\n"); println(evaluationB.clusterResultsToString()); } else { print("Problem during");
println("Here are the results:\n"); println("\nboth methods\n"); println(evaluationB.clusterResultsToString()); } else { print("Problem during");
println("\n=== Full report ===\n"); println("First buildClusterer()"); println(evaluation1A.clusterResultsToString() + "\n\n"); println("Second buildClusterer()"); println(evaluation1B.clusterResultsToString() + "\n\n");
println("\n=== Full report ===\n"); println("First buildClusterer()"); println(evaluation1A.clusterResultsToString() + "\n\n"); println("Second buildClusterer()"); println(evaluation1B.clusterResultsToString() + "\n\n");