Examples with NominalAttribute smile.data.NominalAttribute used on opensource projects

Example 6 with NominalAttribute

use of smile.data.NominalAttribute in project smile by haifengl.

the class LibsvmParser method parse.

/**
     * Parse a libsvm sparse dataset from an input stream.
     * @param name the name of dataset.
     * @param stream the input stream of data.
     * @throws java.io.IOException
     */
public SparseDataset parse(String name, InputStream stream) throws IOException, ParseException {
    BufferedReader reader = new BufferedReader(new InputStreamReader(stream));
    try {
        String line = reader.readLine();
        if (line == null) {
            throw new IOException("Empty data source.");
        }
        String[] tokens = line.trim().split("\\s+");
        boolean classification = true;
        Attribute response = null;
        try {
            Integer.valueOf(tokens[0]);
            response = new NominalAttribute("class");
        } catch (NumberFormatException e) {
            try {
                Double.valueOf(tokens[0]);
                response = new NominalAttribute("response");
                classification = false;
            } catch (NumberFormatException ex) {
                logger.error("Failed to parse {}", tokens[0], ex);
                throw new NumberFormatException("Unrecognized response variable value: " + tokens[0]);
            }
        }
        SparseDataset sparse = new SparseDataset(name, response);
        for (int i = 0; line != null; i++) {
            tokens = line.trim().split("\\s+");
            if (classification) {
                int y = Integer.parseInt(tokens[0]);
                sparse.set(i, y);
            } else {
                double y = Double.parseDouble(tokens[0]);
                sparse.set(i, y);
            }
            for (int k = 1; k < tokens.length; k++) {
                String[] pair = tokens[k].split(":");
                if (pair.length != 2) {
                    throw new NumberFormatException("Invalid data: " + tokens[k]);
                }
                int j = Integer.parseInt(pair[0]) - 1;
                double x = Double.parseDouble(pair[1]);
                sparse.set(i, j, x);
            }
            line = reader.readLine();
        }
        if (classification) {
            int n = sparse.size();
            int[] y = sparse.toArray(new int[n]);
            int[] label = Math.unique(y);
            Arrays.sort(label);
            for (int c : label) {
                response.valueOf(String.valueOf(c));
            }
            for (int i = 0; i < n; i++) {
                sparse.get(i).y = Arrays.binarySearch(label, y[i]);
            }
        }
        return sparse;
    } finally {
        reader.close();
    }
}

Example 7 with NominalAttribute

use of smile.data.NominalAttribute in project smile by haifengl.

the class LDADemo method actionPerformed.

@Override
public void actionPerformed(ActionEvent e) {
    if ("startButton".equals(e.getActionCommand())) {
        datasetIndex = datasetBox.getSelectedIndex();
        if (dataset[datasetIndex] == null) {
            DelimitedTextParser parser = new DelimitedTextParser();
            parser.setDelimiter("[\t]+");
            if (datasetIndex == 0) {
                parser.setColumnNames(true);
            }
            if (datasetIndex == 0) {
                parser.setResponseIndex(new NominalAttribute("class"), 4);
            }
            if (datasetIndex == 1) {
                parser.setResponseIndex(new NominalAttribute("class"), 16);
            }
            try {
                dataset[datasetIndex] = parser.parse(datasetName[datasetIndex], smile.data.parser.IOUtils.getTestDataFile(datasource[datasetIndex]));
            } catch (Exception ex) {
                JOptionPane.showMessageDialog(null, "Failed to load dataset.", "ERROR", JOptionPane.ERROR_MESSAGE);
                System.out.println(ex);
            }
        }
        if (dataset[datasetIndex].size() < 500) {
            pointLegend = 'o';
        } else {
            pointLegend = '.';
        }
        Thread thread = new Thread(this);
        thread.start();
    }
}

Example 8 with NominalAttribute

use of smile.data.NominalAttribute in project smile by haifengl.

the class ProjectionDemo method actionPerformed.

@Override
public void actionPerformed(ActionEvent e) {
    if ("startButton".equals(e.getActionCommand())) {
        datasetIndex = datasetBox.getSelectedIndex();
        if (dataset[datasetIndex] == null) {
            DelimitedTextParser parser = new DelimitedTextParser();
            parser.setDelimiter("[\t]+");
            if (datasetIndex < 5 && datasetIndex != 3) {
                parser.setColumnNames(true);
            }
            if (datasetIndex == 1) {
                parser.setRowNames(true);
            }
            if (datasetIndex == 0) {
                parser.setResponseIndex(new NominalAttribute("class"), 4);
            }
            if (datasetIndex == 3) {
                parser.setResponseIndex(new NominalAttribute("class"), 16);
            }
            if (datasetIndex >= 5) {
                parser.setResponseIndex(new NominalAttribute("class"), 4);
            }
            try {
                dataset[datasetIndex] = parser.parse(datasetName[datasetIndex], smile.data.parser.IOUtils.getTestDataFile(datasource[datasetIndex]));
            } catch (Exception ex) {
                JOptionPane.showMessageDialog(null, "Failed to load dataset.", "ERROR", JOptionPane.ERROR_MESSAGE);
                System.out.println(ex);
            }
        }
        if (dataset[datasetIndex].size() < 500) {
            pointLegend = 'o';
        } else {
            pointLegend = '.';
        }
        Thread thread = new Thread(this);
        thread.start();
    }
}

Example 9 with NominalAttribute

use of smile.data.NominalAttribute in project smile by haifengl.

the class HexmapDemo method main.

public static void main(String[] args) {
    DelimitedTextParser parser = new DelimitedTextParser();
    parser.setResponseIndex(new NominalAttribute("class"), 0);
    try {
        AttributeDataset train = parser.parse("USPS Train", smile.data.parser.IOUtils.getTestDataFile("usps/zip.train"));
        double[][] x = train.toArray(new double[train.size()][]);
        int[] y = train.toArray(new int[train.size()]);
        int m = 20;
        int n = 20;
        SOM som = new SOM(x, m, n);
        String[][] labels = new String[m][n];
        int[] neurons = new int[x.length];
        for (int i = 0; i < x.length; i++) {
            neurons[i] = som.predict(x[i]);
        }
        int[] count = new int[10];
        for (int i = 0; i < m; i++) {
            for (int j = 0; j < n; j++) {
                Arrays.fill(count, 0);
                for (int k = 0; k < neurons.length; k++) {
                    if (neurons[k] == i * n + j) {
                        count[y[k]]++;
                    }
                }
                int sum = Math.sum(count);
                if (sum == 0.0) {
                    labels[i][j] = "no samples";
                } else {
                    labels[i][j] = String.format("<table border=\"1\"><tr><td>Total</td><td align=\"right\">%d</td></tr>", sum);
                    for (int l = 0; l < count.length; l++) {
                        if (count[l] > 0) {
                            labels[i][j] += String.format("<tr><td>class %d</td><td align=\"right\">%.1f%%</td></tr>", l, 100.0 * count[l] / sum);
                        }
                    }
                    labels[i][j] += "</table>";
                }
            }
        }
        double[][] umatrix = som.umatrix();
        double[][][] map = som.map();
        double[][] proximity = new double[m * n][m * n];
        for (int i = 0; i < m * n; i++) {
            for (int j = 0; j < m * n; j++) {
                proximity[i][j] = Math.distance(map[i / n][i % n], map[j / n][j % n]);
            }
        }
        MDS mds = new MDS(proximity, 3);
        double[][] coords = mds.getCoordinates();
        double[][][] mdsgrid = new double[m][n][];
        for (int i = 0; i < m * n; i++) {
            mdsgrid[i / n][i % n] = mds.getCoordinates()[i];
        }
        SammonMapping sammon = new SammonMapping(proximity, coords);
        double[][][] sammongrid = new double[m][n][];
        for (int i = 0; i < m * n; i++) {
            sammongrid[i / n][i % n] = sammon.getCoordinates()[i];
        }
        IsotonicMDS isomds = new IsotonicMDS(proximity, coords);
        double[][][] isomdsgrid = new double[m][n][];
        for (int i = 0; i < m * n; i++) {
            isomdsgrid[i / n][i % n] = isomds.getCoordinates()[i];
        }
        JFrame frame = new JFrame("Hexmap");
        frame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
        frame.setLocationRelativeTo(null);
        frame.add(Hexmap.plot(labels, umatrix));
        PlotCanvas canvas = Surface.plot(mdsgrid);
        canvas.setTitle("MDS");
        frame.add(canvas);
        canvas = Surface.plot(isomdsgrid);
        canvas.setTitle("Isotonic MDS");
        frame.add(canvas);
        canvas = Surface.plot(sammongrid);
        canvas.setTitle("Sammon Mapping");
        frame.add(canvas);
        frame.setVisible(true);
    } catch (Exception ex) {
        System.err.println(ex);
    }
}

Example 10 with NominalAttribute

use of smile.data.NominalAttribute in project smile by haifengl.

the class AdaBoostTest method testUSPS.

/**
     * Test of learn method, of class AdaBoost.
     */
@Test
public void testUSPS() {
    System.out.println("USPS");
    DelimitedTextParser parser = new DelimitedTextParser();
    parser.setResponseIndex(new NominalAttribute("class"), 0);
    try {
        AttributeDataset train = parser.parse("USPS Train", smile.data.parser.IOUtils.getTestDataFile("usps/zip.train"));
        AttributeDataset test = parser.parse("USPS Test", smile.data.parser.IOUtils.getTestDataFile("usps/zip.test"));
        double[][] x = train.toArray(new double[train.size()][]);
        int[] y = train.toArray(new int[train.size()]);
        double[][] testx = test.toArray(new double[test.size()][]);
        int[] testy = test.toArray(new int[test.size()]);
        for (int i = 0; i < y.length; i++) {
            if (y[i] != 0)
                y[i] = 1;
        }
        for (int i = 0; i < testy.length; i++) {
            if (testy[i] != 0)
                testy[i] = 1;
        }
        AdaBoost forest = new AdaBoost(x, y, 100, 6);
        int error = 0;
        for (int i = 0; i < testx.length; i++) {
            if (forest.predict(testx[i]) != testy[i]) {
                error++;
            }
        }
        System.out.println("AdaBoost error = " + error);
        System.out.format("USPS error rate = %.2f%%%n", 100.0 * error / testx.length);
        assertTrue(error <= 25);
    } catch (Exception ex) {
        System.err.println(ex);
    }
}