Examples with Feature org.dkpro.tc.api.features.Feature used on opensource projects

Example 46 with Feature

use of org.dkpro.tc.api.features.Feature in project dkpro-tc by dkpro.

the class WekaUtilTest method tcInstanceToWekaInstanceTest.

@Test
public void tcInstanceToWekaInstanceTest() throws Exception {
    List<String> outcomeValues = Arrays.asList(new String[] { "outc_1", "outc_2", "outc_3" });
    Instance i1 = new Instance();
    i1.addFeature(new Feature("feature1", 2, FeatureType.NUMERIC));
    i1.addFeature(new Feature("feature2", 2, FeatureType.NUMERIC));
    i1.addFeature(new Feature("feature3_{{", "a", FeatureType.STRING));
    Instance i2 = new Instance();
    i2.addFeature(new Feature("feature1", 1, FeatureType.NUMERIC));
    i2.addFeature(new Feature("feature4", "val_1", FeatureType.STRING));
    i2.addFeature(new Feature("feature3_{{", "b", FeatureType.STRING));
    ArrayList<Attribute> attributes = new ArrayList<Attribute>();
    attributes.add(new Attribute("feature5"));
    attributes.add(new Attribute("feature2"));
    attributes.add(new Attribute("feature4", Arrays.asList(new String[] { "val_1", "val_2" })));
    attributes.add(new Attribute("feature1"));
    attributes.add(new Attribute("outcome", outcomeValues));
    Instances trainingData = new Instances("test", attributes, 0);
    weka.core.Instance wekaInstance1 = WekaUtils.tcInstanceToWekaInstance(i1, trainingData, outcomeValues, false);
    weka.core.Instance wekaInstance2 = WekaUtils.tcInstanceToWekaInstance(i2, trainingData, outcomeValues, false);
    assertEquals(true, wekaInstance1.equalHeaders(wekaInstance2));
    assertEquals(5, wekaInstance1.numAttributes());
    wekaInstance1.dataset().add(wekaInstance1);
    wekaInstance2.dataset().add(wekaInstance2);
    System.out.println(wekaInstance1.dataset() + "\n");
    System.out.println(wekaInstance2.dataset() + "\n");
}

Example 47 with Feature

use of org.dkpro.tc.api.features.Feature in project dkpro-tc by dkpro.

the class WekaUtilTest method tcInstanceToWekaInstanceFailTest.

@Test(expected = IllegalArgumentException.class)
public void tcInstanceToWekaInstanceFailTest() throws Exception {
    List<String> outcomeValues = Arrays.asList(new String[] { "outc_1", "outc_2", "outc_3" });
    Instance i1 = new Instance();
    i1.addFeature(new Feature("feature1", 2, FeatureType.NUMERIC));
    i1.addFeature(new Feature("feature4", "val_1", FeatureType.STRING));
    i1.addFeature(new Feature("feature3_{{", "a", FeatureType.STRING));
    ArrayList<Attribute> attributes = new ArrayList<Attribute>();
    attributes.add(new Attribute("feature2"));
    attributes.add(new Attribute("feature4", Arrays.asList(new String[] { "val_4", "val_2" })));
    attributes.add(new Attribute("outcome", outcomeValues));
    Instances trainingData = new Instances("test", attributes, 0);
    @SuppressWarnings("unused") weka.core.Instance wekaInstance1 = WekaUtils.tcInstanceToWekaInstance(i1, trainingData, outcomeValues, false);
}

Example 48 with Feature

use of org.dkpro.tc.api.features.Feature in project dkpro-tc by dkpro.

the class ExtractFeaturesConnector method enforceMatchingFeatures.

private List<Instance> enforceMatchingFeatures(List<Instance> instances) {
    if (!isTesting) {
        return instances;
    }
    List<Instance> out = new ArrayList<>();
    for (Instance i : instances) {
        List<Feature> newFeatures = new ArrayList<>();
        for (Feature feat : i.getFeatures()) {
            if (!featureMeta.getFeatureNames().contains(feat.getName())) {
                continue;
            }
            newFeatures.add(feat);
        }
        i.setFeatures(newFeatures);
        out.add(i);
    }
    return out;
}

Example 49 with Feature

use of org.dkpro.tc.api.features.Feature in project dkpro-tc by dkpro.

the class InstanceExtractor method getSparse.

private Set<Feature> getSparse(JCas jcas, TextClassificationTarget unit, FeatureExtractorResource_ImplBase featExt) throws TextClassificationException {
    Set<Feature> features = ((FeatureExtractor) featExt).extract(jcas, unit);
    Set<Feature> filtered = new HashSet<>();
    for (Feature f : features) {
        if (!f.isDefaultValue()) {
            filtered.add(f);
        }
    }
    return filtered;
}

Example 50 with Feature

use of org.dkpro.tc.api.features.Feature in project dkpro-tc by dkpro.

the class FeatureMetaData method collectMetaData.

public void collectMetaData(List<Instance> instances) {
    featureNames = new TreeSet<>();
    for (Feature f : instances.get(0).getFeatures()) {
        featureNames.add(f.getName());
        if (!featDesc.containsKey(f.getName())) {
            featDesc.put(f.getName(), f.getType());
        }
        if (f.getType() == FeatureType.NOMINAL) {
            enumFeatureName.put(f.getName(), f.getValue().getClass().getName());
        }
    }
    didCollect = true;
}