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Massive On-line Analysis is an environment for massive data mining. MOA
provides a framework for data stream mining and includes tools for evaluation
and a collection of machine learning algorithms. Related to the WEKA project,
also written in Java, while scaling to more demanding problems.
/*
* OutlierAlgoPanel.java
* Copyright (C) 2013 Aristotle University of Thessaloniki, Greece
* @author D. Georgiadis, A. Gounaris, A. Papadopoulos, K. Tsichlas, Y. Manolopoulos
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*
*/
package moa.gui.outliertab;
import java.awt.*;
import java.awt.event.ActionEvent;
import java.awt.event.ActionListener;
import java.util.ArrayList;
import java.util.LinkedList;
import java.util.List;
import java.util.logging.Level;
import java.util.logging.Logger;
import javax.swing.JButton;
import javax.swing.JComponent;
import javax.swing.JLabel;
import javax.swing.JPanel;
import moa.clusterers.outliers.MyBaseOutlierDetector;
import moa.gui.GUIUtils;
import moa.gui.OptionEditComponent;
import moa.options.ClassOption;
import moa.options.Option;
import moa.streams.clustering.ClusteringStream;
public class OutlierAlgoPanel extends javax.swing.JPanel implements ActionListener{
protected List editComponents = new LinkedList();
private ClassOption streamOption = new ClassOption("Stream", 's',
"", ClusteringStream.class,
"RandomRBFGeneratorEvents");
private ClassOption algorithmOption0 = new ClassOption("Algorithm0", 'a',
"Algorithm to use.", MyBaseOutlierDetector.class, "MCOD.MCOD");
private ClassOption algorithmOption1 = new ClassOption("Algorithm1", 'a',
"Algorithm to use.", MyBaseOutlierDetector.class, "Angiulli.ExactSTORM");
public OutlierAlgoPanel() {
initComponents();
}
public void renderAlgoPanel(){
setLayout(new BorderLayout());
ArrayList