Example usage for weka.filters.unsupervised.attribute Discretize setUseEqualFrequency

Introduction

In this page you can find the example usage for weka.filters.unsupervised.attribute Discretize setUseEqualFrequency.

Prototype

public void setUseEqualFrequency(boolean newUseEqualFrequency) 

Source Link

Document

Set the value of UseEqualFrequency.

Usage

From source file:demo.RunGUIProof.java

License:Open Source License

/**
 * @param args//w ww  . j  a v a 2 s  . co  m
 */
public static void main(String[] args) {
    JOptionPane.showMessageDialog(null, introductionMessage, "Chordalysis", JOptionPane.INFORMATION_MESSAGE);

    int result = JOptionPane.showOptionDialog(null, new JTextArea(agreeCitation), "Reference",
            JOptionPane.YES_NO_OPTION, JOptionPane.QUESTION_MESSAGE, null, null, null);
    if (result == JOptionPane.NO_OPTION || result == JOptionPane.CLOSED_OPTION) {
        JOptionPane.showMessageDialog(null,
                "Chordalysis will now stop, because you do not want to reference its source. ", "Chordalysis",
                JOptionPane.WARNING_MESSAGE);
        System.exit(0);
    }

    JFileChooser chooser = new JFileChooser();
    FileNameExtensionFilter filter = new FileNameExtensionFilter("CSV file", "csv");
    chooser.setFileFilter(filter);
    int returnVal = chooser.showOpenDialog(null);
    File csvFile = null;
    if (returnVal == JFileChooser.APPROVE_OPTION) {
        csvFile = chooser.getSelectedFile();
        System.out.println("You chose to open: " + csvFile);
    } else {
        JOptionPane.showMessageDialog(null, noFileSelectedMessage, "Chordalysis", JOptionPane.ERROR_MESSAGE);
        return;
    }
    CSVLoader loader = new CSVLoader();
    if (!csvFile.exists()) {
        JOptionPane.showMessageDialog(null, noFileMessage, "Chordalysis", JOptionPane.INFORMATION_MESSAGE);
        return;
    }
    double pValue = -1;
    while (pValue <= 0 || 1 <= pValue) {
        pValue = Double.valueOf(JOptionPane.showInputDialog("Desired p-value (between 0 and 1)", 0.05));
        if (pValue <= 0 || 1 <= pValue) {
            JOptionPane.showMessageDialog(null, incorrectPValueMessage, "Chordalysis",
                    JOptionPane.WARNING_MESSAGE);
        }
    }

    filter = new FileNameExtensionFilter("PNG or DOT or CSV file or DNE file", "png", "dot", "csv", "dne");
    chooser = new JFileChooser();
    chooser.setFileFilter(filter);
    chooser.setDialogTitle("Where to save the graph?");
    chooser.setSelectedFile(new File(csvFile.getAbsolutePath() + ".png"));
    returnVal = chooser.showSaveDialog(null);
    File graphFile = null;
    if (returnVal == JFileChooser.APPROVE_OPTION) {
        graphFile = chooser.getSelectedFile();
        System.out.println("You chose to save the graph to: " + graphFile.getAbsolutePath());
    } else {
        JOptionPane.showMessageDialog(null, noFileSelectedMessage, "Chordalysis", JOptionPane.ERROR_MESSAGE);
        return;
    }

    try {
        loader.setFile(csvFile);

        returnVal = JOptionPane.showConfirmDialog(null, "Are all of your attribute nominal?", "Chordalysis",
                JOptionPane.YES_NO_OPTION);
        if (returnVal == JOptionPane.YES_OPTION) {
            loader.setNominalAttributes("first-last");
        }

        Instances instances = loader.getDataSet();

        String cols = "";
        for (int i = 0; i < instances.numAttributes(); i++) {
            Attribute att = instances.attribute(i);
            if (!att.isNominal()) {
                cols += (i + 1) + ",";
            }
        }
        if (!cols.isEmpty()) {
            cols = cols.substring(0, cols.length() - 1);
            String message = "Some atributes are not nominal (number " + cols
                    + "), please wait during discretization. ";
            JOptionPane.showMessageDialog(null, message, "Chordalysis", JOptionPane.INFORMATION_MESSAGE);
            Discretize discretizer = new Discretize(cols);
            discretizer.setUseEqualFrequency(true);
            discretizer.setBins(3);
            discretizer.setIgnoreClass(true);
            discretizer.setInputFormat(instances);
            instances = Filter.useFilter(instances, discretizer);
            JOptionPane.showMessageDialog(null, "Discretization is now finished.", "Chordalysis",
                    JOptionPane.INFORMATION_MESSAGE);
        }

        String[] variablesNames = new String[instances.numAttributes()];
        String[][] outcomes = new String[instances.numAttributes()][];
        for (int i = 0; i < variablesNames.length; i++) {
            variablesNames[i] = instances.attribute(i).name();
            outcomes[i] = new String[instances.attribute(i).numValues()];
            for (int j = 0; j < outcomes[i].length; j++) {
                outcomes[i][j] = instances.attribute(i).value(j);
            }
        }

        ChordalysisModelling modeller = new ChordalysisModelling(pValue);
        modeller.buildModel(instances);
        DecomposableModel bestModel = modeller.getModel();
        JOptionPane.showMessageDialog(null, new JTextArea("Chordalysis has now finished analysing your data. "
                + "\nIf you found something useful, please reference Chordalysis as"
                + "\n\t- F. Petitjean, G.I. Webb and A. Nicholson, Scaling log-linear analysis to high-dimensional data, ICDM 2013"
                + "\n\t- F. Petitjean and G.I. Webb, Scaling log-linear analysis to datasets with thousands of variables, SDM 2015"
                + "\n\nYou can find the output file at: '" + graphFile.getAbsolutePath() + "'"), "Citation",
                JOptionPane.INFORMATION_MESSAGE);
        System.out.println("The model selected is:");
        System.out.println(bestModel.toString(variablesNames));
        if (graphFile.getName().endsWith("dot")) {
            bestModel.exportDOT(graphFile, variablesNames);
        } else if (graphFile.getName().endsWith("png")) {
            ImageIO.write(bestModel.getImage(variablesNames), "png", graphFile);
        } else if (graphFile.getName().endsWith("dne")) {
            bestModel.exportBNNetica(graphFile, variablesNames, outcomes);
            bestModel.exportDOT(new File(graphFile.getAbsolutePath() + ".dot"), variablesNames);
            ImageIO.write(bestModel.getImage(variablesNames), "png",
                    new File(graphFile.getAbsolutePath() + ".png"));
            bestModel.saveAssociations(variablesNames, new File(graphFile.getAbsolutePath() + ".csv"));
        } else {
            bestModel.saveAssociations(variablesNames, graphFile);
        }

    } catch (IOException e) {
        JOptionPane.showMessageDialog(null,
                "The file '" + csvFile.getAbsolutePath() + "'\ncannot be read properly.",
                "Error while reading file", JOptionPane.ERROR_MESSAGE);
        System.out.println("I/O error while loading csv file");
        e.printStackTrace();
    } catch (Exception e) {
        JOptionPane.showMessageDialog(null, "Error:" + e.getMessage(), "Chordalysis",
                JOptionPane.ERROR_MESSAGE);
        e.printStackTrace();
    }

}

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