Examples with Feature org.tribuo.Feature used on opensource projects

Example 1 with Feature

use of org.tribuo.Feature in project ml-commons by opensearch-project.

the class AnomalyDetectionLibSVMTest method constructDataFrame.

private DataFrame constructDataFrame(Dataset<Event> data, boolean training, List<Event.EventType> labels) {
    Iterator<Example<Event>> iterator = data.iterator();
    List<ColumnMeta> columns = null;
    DataFrame dataFrame = null;
    while (iterator.hasNext()) {
        Example<Event> example = iterator.next();
        if (columns == null) {
            columns = new ArrayList<>();
            List<ColumnValue> columnValues = new ArrayList<>();
            for (Feature feature : example) {
                columns.add(new ColumnMeta(feature.getName(), ColumnType.DOUBLE));
                columnValues.add(new DoubleValue(feature.getValue()));
            }
            ColumnMeta[] columnMetas = columns.toArray(new ColumnMeta[columns.size()]);
            dataFrame = new DefaultDataFrame(columnMetas);
            addRow(columnValues, training, example, dataFrame, labels);
        } else {
            List<ColumnValue> columnValues = new ArrayList<>();
            for (Feature feature : example) {
                columnValues.add(new DoubleValue(feature.getValue()));
            }
            addRow(columnValues, training, example, dataFrame, labels);
        }
    }
    return dataFrame;
}

Example 2 with Feature

use of org.tribuo.Feature in project ml-commons by opensearch-project.

the class TribuoUtilTest method generateDatasetWithTarget.

@SuppressWarnings("unchecked")
@Test
public void generateDatasetWithTarget() {
    MutableDataset<Regressor> dataset = TribuoUtil.generateDatasetWithTarget(dataFrame, new RegressionFactory(), "test", TribuoOutputType.REGRESSOR, "f2");
    List<Example<Regressor>> examples = dataset.getData();
    Assert.assertEquals(rawData.length, examples.size());
    for (int i = 0; i < rawData.length; ++i) {
        ArrayExample arrayExample = (ArrayExample) examples.get(i);
        Iterator<Feature> iterator = arrayExample.iterator();
        int idx = 1;
        while (iterator.hasNext()) {
            Feature feature = iterator.next();
            Assert.assertEquals("f" + idx, feature.getName());
            Assert.assertEquals(i + idx / 10.0, feature.getValue(), 0.01);
            ++idx;
        }
    }
}

Example 3 with Feature

use of org.tribuo.Feature in project ml-commons by opensearch-project.

the class TribuoUtilTest method generateDataset.

@SuppressWarnings("unchecked")
@Test
public void generateDataset() {
    MutableDataset<ClusterID> dataset = TribuoUtil.generateDataset(dataFrame, new ClusteringFactory(), "test", TribuoOutputType.CLUSTERID);
    List<Example<ClusterID>> examples = dataset.getData();
    Assert.assertEquals(rawData.length, examples.size());
    for (int i = 0; i < rawData.length; ++i) {
        ArrayExample arrayExample = (ArrayExample) examples.get(i);
        Iterator<Feature> iterator = arrayExample.iterator();
        int idx = 1;
        while (iterator.hasNext()) {
            Feature feature = iterator.next();
            Assert.assertEquals("f" + idx, feature.getName());
            Assert.assertEquals(i + idx / 10.0, feature.getValue(), 0.01);
            ++idx;
        }
    }
}