// train SMO and output model SMO classifier = new SMO(); classifier.buildClassifier(trainset);
Instances trainData = ds.getDataset(); //get training dataset SMO sm = new SMO(); //build classifier sm.buildClassifier(data); //train classifier Instances testData = ds.getDataSet(); //now get the test set Evaluation eval = new Evaluation(data); //for recording results eval.evaluateModel(sm, testData); System.out.println(eval.toMatrixString()); //gives the confusion matrix for predictions
private static void build_model() { // TODO Auto-generated method stub try{ // load data ArffLoader loader = new ArffLoader(); loader.setFile(new File("D:\\MAIN PROJECT\\data.arff")); Instances structure = loader.getDataSet(); structure.setClassIndex(structure.numAttributes() - 1); System.out.println("Attributes : "+structure.numAttributes()); System.out.println("Instances : "+structure.numInstances()); // train SMO System.out.println("Before creating smo object"); SMO smo = new SMO(); System.out.println("SMO object created"); smo.buildClassifier(structure); System.out.println("Classifier build"); System.out.println(smo); System.out.println("\nModel build successfully"); } catch(Exception e){ System.out.println("\nstack trace : " + e); } }
smo.buildClassifier(train_data);