Examples with KiePMMLNameValue org.kie.pmml.commons.model.tuples.KiePMMLNameValue used on opensource projects

Example 11 with KiePMMLNameValue

use of org.kie.pmml.commons.model.tuples.KiePMMLNameValue in project drools by kiegroup.

the class MULTIPLE_MODEL_METHODTest method applyWEIGHTED_MAJORITY_VOTE.

@Test(expected = KieEnumException.class)
public void applyWEIGHTED_MAJORITY_VOTE() {
    LinkedHashMap<String, KiePMMLNameValue> inputData = new LinkedHashMap<>();
    Object EXPECTED = 3;
    inputData.put("ValueA", new KiePMMLNameValue("valuea", 1));
    inputData.put("ValueB", new KiePMMLNameValue("valueb", EXPECTED));
    inputData.put("ValueC", new KiePMMLNameValue("valuec", EXPECTED));
    inputData.put("ValueD", new KiePMMLNameValue("valuex", EXPECTED));
    inputData.put("ValueE", new KiePMMLNameValue("valueb", 1));
    WEIGHTED_MAJORITY_VOTE.applyPrediction(inputData);
}

Example 12 with KiePMMLNameValue

use of org.kie.pmml.commons.model.tuples.KiePMMLNameValue in project drools by kiegroup.

the class MULTIPLE_MODEL_METHODTest method applyMAJORITY_VOTE.

@Test
public void applyMAJORITY_VOTE() {
    LinkedHashMap<String, KiePMMLNameValue> inputData = new LinkedHashMap<>();
    Object EXPECTED = 3;
    inputData.put("ValueA", new KiePMMLNameValue("valuea", 1));
    inputData.put("ValueB", new KiePMMLNameValue("valueb", EXPECTED));
    inputData.put("ValueC", new KiePMMLNameValue("valuec", EXPECTED));
    inputData.put("ValueD", new KiePMMLNameValue("valuex", EXPECTED));
    inputData.put("ValueE", new KiePMMLNameValue("valueb", 1));
    Object retrieved = MAJORITY_VOTE.applyPrediction(inputData);
    assertEquals(EXPECTED, retrieved);
    inputData = new LinkedHashMap<>();
    EXPECTED = "EXPECTED";
    inputData.put("ValueA", new KiePMMLNameValue("valuea", "dvsdv"));
    inputData.put("ValueB", new KiePMMLNameValue("valueb", EXPECTED));
    inputData.put("ValueC", new KiePMMLNameValue("valuec", "dssd"));
    inputData.put("ValueD", new KiePMMLNameValue("valuex", EXPECTED));
    inputData.put("ValueE", new KiePMMLNameValue("valueb", "vsd"));
    retrieved = MAJORITY_VOTE.applyPrediction(inputData);
    assertEquals(EXPECTED, retrieved);
}

Example 13 with KiePMMLNameValue

use of org.kie.pmml.commons.model.tuples.KiePMMLNameValue in project drools by kiegroup.

the class MULTIPLE_MODEL_METHODTest method applyMAXNotNumbers.

@Test(expected = KieEnumException.class)
public void applyMAXNotNumbers() {
    LinkedHashMap<String, KiePMMLNameValue> inputData = new LinkedHashMap<>();
    Object EXPECTED = "EXPECTED";
    inputData.put("ValueA", new KiePMMLNameValue("valuea", "dvsdv"));
    inputData.put("ValueB", new KiePMMLNameValue("valueb", EXPECTED));
    inputData.put("ValueC", new KiePMMLNameValue("valuec", "dssd"));
    inputData.put("ValueD", new KiePMMLNameValue("valuex", EXPECTED));
    inputData.put("ValueE", new KiePMMLNameValue("valueb", "vsd"));
    MAX.applyPrediction(inputData);
}

Example 14 with KiePMMLNameValue

use of org.kie.pmml.commons.model.tuples.KiePMMLNameValue in project drools by kiegroup.

the class MULTIPLE_MODEL_METHODTest method applySELECT_FIRSTNotNumbers.

@Test
public void applySELECT_FIRSTNotNumbers() {
    LinkedHashMap<String, KiePMMLNameValue> inputData = new LinkedHashMap<>();
    Object EXPECTED = "EXPECTED";
    inputData.put("ValueA", new KiePMMLNameValue("valuea", EXPECTED));
    inputData.put("ValueB", new KiePMMLNameValue("valueb", "vdsvsd"));
    inputData.put("ValueC", new KiePMMLNameValue("valuec", "dssd"));
    inputData.put("ValueD", new KiePMMLNameValue("valuex", "vfdsvsdeeee"));
    inputData.put("ValueE", new KiePMMLNameValue("valueb", "vsd"));
    Object retrieved = SELECT_FIRST.applyPrediction(inputData);
    assertEquals(EXPECTED, retrieved);
}

Example 15 with KiePMMLNameValue

use of org.kie.pmml.commons.model.tuples.KiePMMLNameValue in project drools by kiegroup.

the class MULTIPLE_MODEL_METHODTest method applySELECT_ALLNumbers.

@Test
public void applySELECT_ALLNumbers() {
    Map<String, Object> expectedKiePMMLValueWeightMap = getExpectedKiePMMLValueWeightMap(true);
    LinkedHashMap<String, KiePMMLNameValue> inputData = (LinkedHashMap<String, KiePMMLNameValue>) expectedKiePMMLValueWeightMap.get("inputData");
    List<Double> expected = inputData.values().stream().map(kiePMMLNameValue -> ((KiePMMLValueWeight) kiePMMLNameValue.getValue()).getValue()).collect(Collectors.toList());
    List retrieved = (List) SELECT_ALL.applyPrediction(inputData);
    assertEquals(expected.size(), retrieved.size());
    for (Double expDouble : expected) {
        assertTrue(retrieved.contains(expDouble));
    }
    expectedKiePMMLValueWeightMap = getExpectedKiePMMLValueWeightMap(false);
    inputData = (LinkedHashMap<String, KiePMMLNameValue>) expectedKiePMMLValueWeightMap.get("inputData");
    expected = inputData.values().stream().map(kiePMMLNameValue -> ((KiePMMLValueWeight) kiePMMLNameValue.getValue()).getValue()).collect(Collectors.toList());
    retrieved = (List) SELECT_ALL.applyPrediction(inputData);
    assertEquals(expected.size(), retrieved.size());
    for (Double expDouble : expected) {
        assertTrue(retrieved.contains(expDouble));
    }
}