Examples with TreeEnsembleLearnerConfiguration org.knime.base.node.mine.treeensemble2.node.learner.TreeEnsembleLearnerConfiguration used on opensource projects

Example 36 with TreeEnsembleLearnerConfiguration

use of org.knime.base.node.mine.treeensemble2.node.learner.TreeEnsembleLearnerConfiguration in project knime-core by knime.

the class SurrogatesTest method createSplitCandidates.

private static SplitCandidate[] createSplitCandidates(final TreeEnsembleLearnerConfiguration config) {
    double[] colBestData = TreeNumericColumnDataTest.asDataArray(COLBEST);
    double[] col1Data = TreeNumericColumnDataTest.asDataArray(COL1);
    double[] col2Data = TreeNumericColumnDataTest.asDataArray(COL2);
    TreeOrdinaryNumericColumnData colBest = TreeNumericColumnDataTest.createNumericColumnData(config, colBestData, "colBest", 0);
    colBest.getMetaData().setAttributeIndex(0);
    TreeOrdinaryNumericColumnData col1 = TreeNumericColumnDataTest.createNumericColumnData(config, col1Data, "col1", 1);
    col1.getMetaData().setAttributeIndex(1);
    TreeOrdinaryNumericColumnData col2 = TreeNumericColumnDataTest.createNumericColumnData(config, col2Data, "col2", 2);
    col2.getMetaData().setAttributeIndex(2);
    NumericSplitCandidate splitBest = new NumericSplitCandidate(colBest, SPLITVAL, 0.5, createMissingBitSet(colBestData), NumericSplitCandidate.NO_MISSINGS);
    NumericSplitCandidate split1 = new NumericSplitCandidate(col1, SPLITVAL, 0.25, createMissingBitSet(col1Data), NumericSplitCandidate.NO_MISSINGS);
    NumericSplitCandidate split2 = new NumericSplitCandidate(col2, SPLITVAL, 0.1, createMissingBitSet(col2Data), NumericSplitCandidate.NO_MISSINGS);
    return new SplitCandidate[] { splitBest, split1, split2 };
}

Example 37 with TreeEnsembleLearnerConfiguration

use of org.knime.base.node.mine.treeensemble2.node.learner.TreeEnsembleLearnerConfiguration in project knime-core by knime.

the class TreeNodeNominalConditionTest method testToPMMLPredicate.

/**
 * This method tests the {@link TreeNodeNominalCondition#toPMMLPredicate()} method.
 *
 * @throws Exception
 */
@Test
public void testToPMMLPredicate() throws Exception {
    final TreeEnsembleLearnerConfiguration config = new TreeEnsembleLearnerConfiguration(false);
    final TestDataGenerator dataGen = new TestDataGenerator(config);
    final TreeNominalColumnData col = dataGen.createNominalAttributeColumn("A,A,B,C,C,D", "testcol", 0);
    TreeNodeNominalCondition cond = new TreeNodeNominalCondition(col.getMetaData(), 3, false);
    PMMLPredicate predicate = cond.toPMMLPredicate();
    assertThat(predicate, instanceOf(PMMLSimplePredicate.class));
    PMMLSimplePredicate simplePredicate = (PMMLSimplePredicate) predicate;
    assertEquals("Wrong operator", PMMLOperator.EQUAL, simplePredicate.getOperator());
    assertEquals("Wrong split value", "D", simplePredicate.getThreshold());
    cond = new TreeNodeNominalCondition(col.getMetaData(), 0, true);
    predicate = cond.toPMMLPredicate();
    assertThat(predicate, instanceOf(PMMLCompoundPredicate.class));
    PMMLCompoundPredicate compound = (PMMLCompoundPredicate) predicate;
    assertEquals("Wrong boolean operator.", PMMLBooleanOperator.OR, compound.getBooleanOperator());
    List<PMMLPredicate> preds;
    preds = compound.getPredicates();
    assertEquals("Wrong number of predicates in compound predicate.", 2, preds.size());
    assertThat(preds.get(0), instanceOf(PMMLSimplePredicate.class));
    simplePredicate = (PMMLSimplePredicate) preds.get(0);
    assertEquals("Wrong operator", PMMLOperator.EQUAL, simplePredicate.getOperator());
    assertEquals("Wrong split value", "A", simplePredicate.getThreshold());
    assertEquals("Wrong attribute.", col.getMetaData().getAttributeName(), simplePredicate.getSplitAttribute());
    assertThat(preds.get(1), instanceOf(PMMLSimplePredicate.class));
    simplePredicate = (PMMLSimplePredicate) preds.get(1);
    assertEquals("Should be isMissing", PMMLOperator.IS_MISSING, simplePredicate.getOperator());
}

Example 38 with TreeEnsembleLearnerConfiguration

use of org.knime.base.node.mine.treeensemble2.node.learner.TreeEnsembleLearnerConfiguration in project knime-core by knime.

the class TreeNodeNominalConditionTest method testTestCondition.

/**
 * This method tests the
 * {@link TreeNodeNominalCondition#testCondition(org.knime.base.node.mine.treeensemble2.data.PredictorRecord)}
 * method
 *
 * @throws Exception
 */
@Test
public void testTestCondition() throws Exception {
    final TreeEnsembleLearnerConfiguration config = new TreeEnsembleLearnerConfiguration(false);
    final TestDataGenerator dataGen = new TestDataGenerator(config);
    final TreeNominalColumnData col = dataGen.createNominalAttributeColumn("A,A,B,C,C,D", "testcol", 0);
    TreeNodeNominalCondition cond = new TreeNodeNominalCondition(col.getMetaData(), 3, false);
    final Map<String, Object> map = Maps.newHashMap();
    final String colName = col.getMetaData().getAttributeName();
    map.put(colName, 0);
    final PredictorRecord record = new PredictorRecord(map);
    assertFalse("The value A was falsely accepted", cond.testCondition(record));
    map.clear();
    map.put(colName, 1);
    assertFalse("The value B was falsely accepted", cond.testCondition(record));
    map.clear();
    map.put(colName, 2);
    assertFalse("The value C was falsely accepted", cond.testCondition(record));
    map.clear();
    map.put(colName, 3);
    assertTrue("The value D was falsely rejected", cond.testCondition(record));
    map.clear();
    map.put(colName, PredictorRecord.NULL);
    assertFalse("Missing values were falsely accepted", cond.testCondition(record));
    cond = new TreeNodeNominalCondition(col.getMetaData(), 0, true);
    map.clear();
    map.put(colName, 0);
    assertTrue("The value A was falsely rejected", cond.testCondition(record));
    map.clear();
    map.put(colName, 1);
    assertFalse("The value B was falsely accepted", cond.testCondition(record));
    map.clear();
    map.put(colName, 2);
    assertFalse("The value C was falsely accepted", cond.testCondition(record));
    map.clear();
    map.put(colName, 3);
    assertFalse("The value D was falsely accepted", cond.testCondition(record));
    map.clear();
    map.put(colName, PredictorRecord.NULL);
    assertTrue("Missing values were falsely rejected", cond.testCondition(record));
}

Example 39 with TreeEnsembleLearnerConfiguration

use of org.knime.base.node.mine.treeensemble2.node.learner.TreeEnsembleLearnerConfiguration in project knime-core by knime.

the class TreeEnsembleClassificationLearnerNodeDialogPane method loadSettingsFrom.

/**
 * {@inheritDoc}
 */
@Override
protected void loadSettingsFrom(final NodeSettingsRO settings, final DataTableSpec[] specs) throws NotConfigurableException {
    final DataTableSpec inSpec = specs[0];
    TreeEnsembleLearnerConfiguration cfg = new TreeEnsembleLearnerConfiguration(false);
    cfg.loadInDialog(settings, inSpec);
    m_attributeSelectionPanel.loadSettingsFrom(inSpec, cfg);
    m_treeOptionsPanel.loadSettingsFrom(inSpec, cfg);
    m_ensembleOptionsPanel.loadSettings(cfg);
}

Example 40 with TreeEnsembleLearnerConfiguration

use of org.knime.base.node.mine.treeensemble2.node.learner.TreeEnsembleLearnerConfiguration in project knime-core by knime.

the class TreeEnsembleClassificationLearnerNodeModel method loadValidatedSettingsFrom.

/**
 * {@inheritDoc}
 */
@Override
protected void loadValidatedSettingsFrom(final NodeSettingsRO settings) throws InvalidSettingsException {
    TreeEnsembleLearnerConfiguration config = new TreeEnsembleLearnerConfiguration(false);
    config.loadInModel(settings);
    m_configuration = config;
}