Examples with FeatureVector com.airbnb.aerosolve.core.FeatureVector used on opensource projects

Example 6 with FeatureVector

use of com.airbnb.aerosolve.core.FeatureVector in project aerosolve by airbnb.

the class LowRankLinearModelTest method testScoreNonEmptyFeature.

@Test
public void testScoreNonEmptyFeature() {
    FeatureVector animalFv = makeFeatureVector("animal");
    FeatureVector colorFv = makeFeatureVector("color");
    FeatureVector fruitFv = makeFeatureVector("fruit");
    LowRankLinearModel model = makeLowRankLinearModel();
    ArrayList<MulticlassScoringResult> s1 = model.scoreItemMulticlass(animalFv);
    assertEquals(s1.size(), 3);
    assertEquals(0.0f, s1.get(0).score, 3.0f);
    assertEquals(0.0f, s1.get(1).score, 1e-10f);
    assertEquals(0.0f, s1.get(2).score, 1e-10f);
    ArrayList<MulticlassScoringResult> s2 = model.scoreItemMulticlass(colorFv);
    assertEquals(s2.size(), 3);
    assertEquals(0.0f, s2.get(0).score, 1e-10f);
    assertEquals(0.0f, s2.get(1).score, 6.0f);
    assertEquals(0.0f, s2.get(2).score, 1e-10f);
    ArrayList<MulticlassScoringResult> s3 = model.scoreItemMulticlass(fruitFv);
    assertEquals(s3.size(), 3);
    assertEquals(0.0f, s3.get(0).score, 1e-10f);
    assertEquals(0.0f, s3.get(1).score, 1e-10f);
    assertEquals(0.0f, s3.get(2).score, 4.0f);
}

Example 7 with FeatureVector

use of com.airbnb.aerosolve.core.FeatureVector in project aerosolve by airbnb.

the class LowRankLinearModelTest method testScoreEmptyFeature.

@Test
public void testScoreEmptyFeature() {
    FeatureVector featureVector = new FeatureVector();
    LowRankLinearModel model = makeLowRankLinearModel();
    ArrayList<MulticlassScoringResult> score = model.scoreItemMulticlass(featureVector);
    assertEquals(score.size(), 3);
    assertEquals(0.0f, score.get(0).score, 1e-10f);
    assertEquals(0.0f, score.get(1).score, 1e-10f);
    assertEquals(0.0f, score.get(2).score, 1e-10f);
}

Example 8 with FeatureVector

use of com.airbnb.aerosolve.core.FeatureVector in project aerosolve by airbnb.

the class LowRankLinearModelTest method makeFeatureVector.

public FeatureVector makeFeatureVector(String label) {
    FeatureVector featureVector = new FeatureVector();
    HashMap stringFeatures = new HashMap<String, HashSet<String>>();
    featureVector.setStringFeatures(stringFeatures);
    HashMap floatFeatures = new HashMap<String, HashMap<String, Double>>();
    featureVector.setFloatFeatures(floatFeatures);
    HashMap feature = new HashMap<String, Float>();
    switch(label) {
        case "animal":
            {
                feature.put("cat", 1.0);
                feature.put("dog", 2.0);
                floatFeatures.put("a", feature);
                break;
            }
        case "color":
            {
                feature.put("red", 2.0);
                feature.put("black", 4.0);
                floatFeatures.put("c", feature);
                break;
            }
        case "fruit":
            {
                feature.put("apple", 1.0);
                feature.put("kiwi", 3.0);
                floatFeatures.put("f", feature);
                break;
            }
        default:
            break;
    }
    return featureVector;
}

Example 9 with FeatureVector

use of com.airbnb.aerosolve.core.FeatureVector in project aerosolve by airbnb.

the class ModelScorerTest method rawProbability.

@Test
public void rawProbability() throws Exception {
    ModelConfig incomeModel = ModelConfig.builder().modelName("income.model").configName("income_prediction.conf").key("spline_model").build();
    ModelScorer modelScorer = new ModelScorer(incomeModel);
    FeatureMapping featureMapping = new FeatureMapping();
    featureMapping.add(dataName1);
    featureMapping.add(dataName2);
    featureMapping.add(dataName3);
    featureMapping.finish();
    FeatureGen f = new FeatureGen(featureMapping);
    f.add(data1, dataName1);
    f.add(data2, dataName2);
    f.add(data3, dataName3);
    Features features = f.gen();
    List<StringFamily> stringFamilies = new ArrayList<>();
    stringFamilies.add(new StringFamily("S"));
    List<FloatFamily> floatFamilies = new ArrayList<>();
    floatFamilies.add(new FloatFamily("F"));
    Example example = FeatureVectorGen.toSingleFeatureVectorExample(features, stringFamilies, floatFamilies);
    FeatureVector featureVector = example.getExample().get(0);
    final Map<String, Map<String, Double>> floatFeatures = featureVector.getFloatFeatures();
    Map<String, Double> floatFeatureFamily = floatFeatures.get("F");
    assertEquals(floatFeatureFamily.get("age"), 30, 0.1);
    assertEquals(floatFeatureFamily.get("hours"), 40, 0.1);
    final Map<String, Set<String>> stringFeatures = featureVector.getStringFeatures();
    Set<String> stringFeatureFamily = stringFeatures.get("S");
    assertFalse(stringFeatureFamily.contains("marital-status"));
    assertTrue(stringFeatureFamily.contains("married"));
    double score = modelScorer.score(example);
    log.info("score {}", score);
}

Example 10 with FeatureVector

use of com.airbnb.aerosolve.core.FeatureVector in project aerosolve by airbnb.

the class AdditiveModelTest method testScoreEmptyFeature.

@Test
public void testScoreEmptyFeature() {
    FeatureVector featureVector = new FeatureVector();
    AdditiveModel model = new AdditiveModel();
    float score = model.scoreItem(featureVector);
    assertEquals(0.0f, score, 1e-10f);
}