Java Code Examples for meka.core.Result#getMeasurement()

public static void main(String[] args) throws Exception {
  if (args.length != 1)
    throw new IllegalArgumentException("Required arguments: <dataset>");

  System.out.println("Loading data: " + args[0]);
  Instances data = DataSource.read(args[0]);
  MLUtils.prepareData(data);

  System.out.println("Cross-validate BR classifier");
  BR classifier = new BR();
  // further configuration of classifier
  String top = "PCut1";
  String vop = "3";
  Result result = Evaluation.cvModel(classifier, data, 10, top, vop);

  JFrame frame = new JFrame("Micro curve");
  frame.setDefaultCloseOperation(JDialog.EXIT_ON_CLOSE);
  frame.getContentPane().setLayout(new BorderLayout());
  Instances performance = (Instances) result.getMeasurement(CURVE_DATA_MICRO);
  try {
    VisualizePanel panel = createPanel(performance);
    frame.getContentPane().add(panel, BorderLayout.CENTER);
  }
  catch (Exception ex) {
    System.err.println("Failed to create plot!");
    ex.printStackTrace();
  }
  frame.setSize(800, 600);
  frame.setLocationRelativeTo(null);
  frame.setVisible(true);
}
 

/**
 * Returns the action lister to use in the menu.
 *
 * @param history   the current history
 * @param index     the selected history item
 * @return          the listener
 */
@Override
public ActionListener getActionListener(final ResultHistoryList history, final int index) {
	final Result result = history.getResultAt(index);

	return new ActionListener() {
		@Override
		public void actionPerformed(ActionEvent e) {
			JDialog dialog = new JDialog((Frame) null, history.getSuffixAt(index), false);
			dialog.setDefaultCloseOperation(JDialog.DISPOSE_ON_CLOSE);
			dialog.getContentPane().setLayout(new BorderLayout());
			Instances performance = (Instances) result.getMeasurement(CURVE_DATA_MACRO);
			try {
				VisualizePanel panel = createPanel(performance);
				dialog.getContentPane().add(panel, BorderLayout.CENTER);
			}
			catch (Exception ex) {
				System.err.println("Failed to create plot!");
				ex.printStackTrace();
			}
			dialog.setSize(800, 600);
			dialog.setLocationRelativeTo(null);
			dialog.setVisible(true);
		}
	};
}
 

/**
 * Returns the action lister to use in the menu.
 *
 * @param history   the current history
 * @param index     the selected history item
 * @return          the listener
 */
@Override
public ActionListener getActionListener(final ResultHistoryList history, final int index) {
	final Result result = history.getResultAt(index);

	return new ActionListener() {
		@Override
		public void actionPerformed(ActionEvent e) {
			JDialog dialog = new JDialog((Frame) null, history.getSuffixAt(index), false);
			dialog.setDefaultCloseOperation(JDialog.DISPOSE_ON_CLOSE);
			dialog.getContentPane().setLayout(new BorderLayout());
			Instances performance = (Instances) result.getMeasurement(RESULTS_SAMPLED_OVER_TIME);
			try {
				VisualizePanel panel = createPanel(performance);
				dialog.getContentPane().add(panel, BorderLayout.CENTER);
			}
			catch (Exception ex) {
				System.err.println("Failed to create plot!");
				ex.printStackTrace();
			}
			dialog.setSize(800, 600);
			dialog.setLocationRelativeTo(null);
			dialog.setVisible(true);
		}
	};
}
 

/**
 * Returns the action lister to use in the menu.
 *
 * @param history   the current history
 * @param index     the selected history item
 * @return          the listener
 */
@Override
public ActionListener getActionListener(final ResultHistoryList history, final int index) {
	final Result result = history.getResultAt(index);

	return new ActionListener() {
		@Override
		public void actionPerformed(ActionEvent e) {
			JDialog dialog = new JDialog((Frame) null, history.getSuffixAt(index), false);
			dialog.setDefaultCloseOperation(JDialog.DISPOSE_ON_CLOSE);
			dialog.getContentPane().setLayout(new BorderLayout());
			Instances performance = (Instances) result.getMeasurement(CURVE_DATA_MICRO);
			try {
				VisualizePanel panel = createPanel(performance);
				dialog.getContentPane().add(panel, BorderLayout.CENTER);
			}
			catch (Exception ex) {
				System.err.println("Failed to create plot!");
				ex.printStackTrace();
			}
			dialog.setSize(800, 600);
			dialog.setLocationRelativeTo(null);
			dialog.setVisible(true);
		}
	};
}
 

public void testDeepML() {
	System.out.println("Test Stacked Boltzmann Machines with an off-the-shelf multi-label classifier");
	DeepML dbn = new DeepML();

	MCC h = new MCC();
	SMO smo = new SMO();
	smo.setBuildCalibrationModels(true);
	h.setClassifier(smo);

	dbn.setClassifier(h);
	dbn.setE(100);
	dbn.setH(30);

	Result r = EvaluationTests.cvEvaluateClassifier(dbn);
	System.out.println("DeepML + MCC" + r.getMeasurement("Accuracy"));
	String s = (String)r.getMeasurement("Accuracy");
	assertTrue("DeepML+MCC Accuracy Correct", s.startsWith("0.53")); // Good enough 
}
 

public void testDBPNN() {
	
	System.out.println("Test Back Prop Neural Network with pre-trained weights (via RBM)");
	DBPNN dbn = new DBPNN();
	dbn.setClassifier(new BPNN());
	dbn.setDebug(true);

	try {
		dbn.setOptions(Utils.splitOptions("-H 30 -E 500 -r 0.1 -m 0.2"));
	} catch(Exception e) {
		System.err.println("Fatal Error");
		e.printStackTrace();
		System.exit(1);
	}
	Result r = EvaluationTests.cvEvaluateClassifier(dbn);
	String s = (String)r.getMeasurement("Accuracy");
	System.out.println("DBPNN + _" + r.getMeasurement("Accuracy"));
	assertTrue("DBPNN Accuracy Correct", s.equals("0.556 +/- 0.038"));
}
 

public static void main(String[] args) throws Exception {
  if (args.length != 1)
    throw new IllegalArgumentException("Required arguments: <dataset>");

  System.out.println("Loading data: " + args[0]);
  Instances data = DataSource.read(args[0]);
  MLUtils.prepareData(data);

  System.out.println("Cross-validate BR classifier");
  BR classifier = new BR();
  // further configuration of classifier
  String top = "PCut1";
  String vop = "3";
  Result result = Evaluation.cvModel(classifier, data, 10, top, vop);

  JFrame frame = new JFrame("ROC");
  frame.setDefaultCloseOperation(JDialog.EXIT_ON_CLOSE);
  frame.getContentPane().setLayout(new BorderLayout());
  JTabbedPane tabbed = new JTabbedPane();
  frame.getContentPane().add(tabbed, BorderLayout.CENTER);
  Instances[] curves = (Instances[]) result.getMeasurement(CURVE_DATA);
  for (int i = 0; i < curves.length; i++) {
    try {
      ThresholdVisualizePanel panel = createPanel(curves[i], "Label " + i);
      tabbed.addTab("" + i, panel);
    }
    catch (Exception ex) {
      System.err.println("Failed to create plot for label " + i);
      ex.printStackTrace();
    }
  }
  frame.setSize(800, 600);
  frame.setLocationRelativeTo(null);
  frame.setVisible(true);
}
 

public static void main(String[] args) throws Exception {
  if (args.length != 1)
    throw new IllegalArgumentException("Required arguments: <dataset>");

  System.out.println("Loading data: " + args[0]);
  Instances data = DataSource.read(args[0]);
  MLUtils.prepareData(data);

  System.out.println("Cross-validate BR classifier");
  BR classifier = new BR();
  // further configuration of classifier
  String top = "PCut1";
  String vop = "3";
  Result result = Evaluation.cvModel(classifier, data, 10, top, vop);

  JFrame frame = new JFrame("Macro curve");
  frame.setDefaultCloseOperation(JDialog.EXIT_ON_CLOSE);
  frame.getContentPane().setLayout(new BorderLayout());
  Instances performance = (Instances) result.getMeasurement(CURVE_DATA_MACRO);
  try {
    VisualizePanel panel = createPanel(performance);
    frame.getContentPane().add(panel, BorderLayout.CENTER);
  }
  catch (Exception ex) {
    System.err.println("Failed to create plot!");
    ex.printStackTrace();
  }
  frame.setSize(800, 600);
  frame.setLocationRelativeTo(null);
  frame.setVisible(true);
}
 

public static void main(String[] args) throws Exception {
  if (args.length != 1)
    throw new IllegalArgumentException("Required arguments: <dataset>");

  System.out.println("Loading data: " + args[0]);
  Instances data = DataSource.read(args[0]);
  MLUtils.prepareData(data);

  System.out.println("Cross-validate BR classifier");
  BR classifier = new BR();
  // further configuration of classifier
  String top = "PCut1";
  String vop = "3";
  Result result = Evaluation.cvModel(classifier, data, 10, top, vop);

  JFrame frame = new JFrame("Precision-recall");
  frame.setDefaultCloseOperation(JDialog.EXIT_ON_CLOSE);
  frame.getContentPane().setLayout(new BorderLayout());
  JTabbedPane tabbed = new JTabbedPane();
  frame.getContentPane().add(tabbed, BorderLayout.CENTER);
  Instances[] curves = (Instances[]) result.getMeasurement(CURVE_DATA);
  for (int i = 0; i < curves.length; i++) {
    try {
      ThresholdVisualizePanel panel = createPanel(curves[i], "Label " + i);
      tabbed.addTab("" + i, panel);
    }
    catch (Exception ex) {
      System.err.println("Failed to create plot for label " + i);
      ex.printStackTrace();
    }
  }
  frame.setSize(800, 600);
  frame.setLocationRelativeTo(null);
  frame.setVisible(true);
}
 

/**
 * Returns the action lister to use in the menu.
 *
 * @param history   the current history
 * @param index     the selected history item
 * @return          the listener
 */
@Override
public ActionListener getActionListener(final ResultHistoryList history, final int index) {
	final Result result = history.getResultAt(index);

	return new ActionListener() {
		@Override
		public void actionPerformed(ActionEvent e) {
			Instances performance = (Instances) result.getMeasurement(IncrementalPerformance.RESULTS_SAMPLED_OVER_TIME);

			int retVal = getFileChooser().showSaveDialog(null);
			if (retVal != MekaFileChooser.APPROVE_OPTION)
				return;
			File file = getFileChooser().getSelectedFile();


			try {

				CSVSaver saver = new CSVSaver();
				saver.setInstances(performance);
				saver.setFile(getFileChooser().getSelectedFile());
				saver.writeBatch();
			} catch (Exception ex) {
				String msg = "Failed to write to '" + file + "'!";
				System.err.println(msg);
				ex.printStackTrace();
				JOptionPane.showMessageDialog( null, msg + "\n" + e);
			}
		}
	};
}
 

/**
 * Returns the action lister to use in the menu.
 *
 * @param history   the current history
 * @param index     the selected history item
 * @return          the listener
 */
@Override
public ActionListener getActionListener(final ResultHistoryList history, final int index) {
	final Result result = history.getResultAt(index);

	return new ActionListener() {
		@Override
		public void actionPerformed(ActionEvent e) {
			JDialog dialog = new JDialog((Frame) null, history.getSuffixAt(index), false);
			dialog.setDefaultCloseOperation(JDialog.DISPOSE_ON_CLOSE);
			JTabbedPane tabbed = new JTabbedPane();
			dialog.getContentPane().setLayout(new BorderLayout());
			dialog.getContentPane().add(tabbed, BorderLayout.CENTER);
			Instances[] curves = (Instances[]) result.getMeasurement(CURVE_DATA);
			for (int i = 0; i < curves.length; i++) {
				try {
					ThresholdVisualizePanel panel = createPanel(curves[i], "Label " + i);
					tabbed.addTab("" + i, panel);
				}
				catch (Exception ex) {
					System.err.println("Failed to create plot for label " + i);
					ex.printStackTrace();
				}
			}
			dialog.setSize(800, 600);
			dialog.setLocationRelativeTo(null);
			dialog.setVisible(true);
		}
	};
}
 

public void testLC() {

		Result r = null;

		// Test LC
		LC lc = new LC();
		lc.setClassifier(new SMO());
		r = EvaluationTests.cvEvaluateClassifier(lc);
		String s = (String)r.getMeasurement("Accuracy");
		System.out.println("LC "+s);
		TestHelper.assertAlmostEquals("LC Accuracy Correct", "0.568 +/- 0.032", (String)s, 1);

		// Test PS (0,0) -- should be identical
		PS ps = new PS();
		ps.setClassifier(new SMO());
		r = EvaluationTests.cvEvaluateClassifier(ps);
		System.out.println("PS "+r.getMeasurement("Accuracy"));
		assertTrue("PS(0,0) Accuracy Identical to LC", s.equals(r.getMeasurement("Accuracy")));

		// Test PS (3,1) -- should be faster 
		ps.setP(3);
		ps.setN(1);

		r = EvaluationTests.cvEvaluateClassifier(ps);
		System.out.println("PS(3,1) "+r.getMeasurement("Accuracy"));
		TestHelper.assertAlmostEquals("PS(3,1) Accuracy Correct", "0.565 +/- 0.04", (String)r.getMeasurement("Accuracy"), 1);

		// Test EPS
		EnsembleML eps = new EnsembleML();
		eps.setClassifier(ps);
		r = EvaluationTests.cvEvaluateClassifier(eps);
		System.out.println("EPS "+r.getMeasurement("Accuracy"));
		TestHelper.assertAlmostEquals("EPS Accuracy Correct", "0.574 +/- 0.042", (String)r.getMeasurement("Accuracy"), 1);
	}