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

Example 1 with TreeEnsembleLearnerConfiguration

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

the class RandomForestClassificationLearnerNodeDialogPane method saveSettingsTo.

/**
 * {@inheritDoc}
 */
@Override
protected void saveSettingsTo(final NodeSettingsWO settings) throws InvalidSettingsException {
    TreeEnsembleLearnerConfiguration cfg = new TreeEnsembleLearnerConfiguration(false);
    m_optionPanel.saveSettings(cfg);
    cfg.save(settings);
}

Example 2 with TreeEnsembleLearnerConfiguration

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

the class RandomForestClassificationLearnerNodeModel method loadValidatedSettingsFrom.

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

Example 3 with TreeEnsembleLearnerConfiguration

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

the class TreeLearnerClassification method learnSingleTree.

/**
 * {@inheritDoc}
 */
@Override
public TreeModelClassification learnSingleTree(final ExecutionMonitor exec, final RandomData rd) throws CanceledExecutionException {
    final TreeData data = getData();
    final RowSample rowSampling = getRowSampling();
    final TreeEnsembleLearnerConfiguration config = getConfig();
    final TreeTargetNominalColumnData targetColumn = (TreeTargetNominalColumnData) data.getTargetColumn();
    double[] dataMemberships = new double[data.getNrRows()];
    for (int i = 0; i < dataMemberships.length; i++) {
        // dataMemberships[i] = m_rowSampling.getCountFor(i) > 0 ? 1.0 : 0.0;
        dataMemberships[i] = rowSampling.getCountFor(i);
    }
    ClassificationPriors targetPriors = targetColumn.getDistribution(dataMemberships, config);
    BitSet forbiddenColumnSet = new BitSet(data.getNrAttributes());
    // TreeNodeMembershipController rootMembershipController = new TreeNodeMembershipController(data, dataMemberships);
    TreeNodeMembershipController rootMembershipController = null;
    TreeNodeClassification rootNode = buildTreeNode(exec, 0, dataMemberships, TreeNodeSignature.ROOT_SIGNATURE, targetPriors, forbiddenColumnSet, rootMembershipController);
    assert forbiddenColumnSet.cardinality() == 0;
    rootNode.setTreeNodeCondition(TreeNodeTrueCondition.INSTANCE);
    return new TreeModelClassification(rootNode);
}

Example 4 with TreeEnsembleLearnerConfiguration

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

the class TreeLearnerClassification method findBestSplitClassification.

private SplitCandidate findBestSplitClassification(final int currentDepth, final double[] rowSampleWeights, final TreeNodeSignature treeNodeSignature, final ClassificationPriors targetPriors, final BitSet forbiddenColumnSet, final TreeNodeMembershipController membershipController) {
    final TreeData data = getData();
    final ColumnSampleStrategy colSamplingStrategy = getColSamplingStrategy();
    final TreeEnsembleLearnerConfiguration config = getConfig();
    final int maxLevels = config.getMaxLevels();
    if (maxLevels != TreeEnsembleLearnerConfiguration.MAX_LEVEL_INFINITE && currentDepth >= maxLevels) {
        return null;
    }
    final int minNodeSize = config.getMinNodeSize();
    if (minNodeSize != TreeEnsembleLearnerConfiguration.MIN_NODE_SIZE_UNDEFINED) {
        if (targetPriors.getNrRecords() < minNodeSize) {
            return null;
        }
    }
    final double priorImpurity = targetPriors.getPriorImpurity();
    if (priorImpurity < TreeColumnData.EPSILON) {
        return null;
    }
    final TreeTargetNominalColumnData targetColumn = (TreeTargetNominalColumnData) data.getTargetColumn();
    SplitCandidate splitCandidate = null;
    if (currentDepth == 0 && config.getHardCodedRootColumn() != null) {
        final TreeAttributeColumnData rootColumn = data.getColumn(config.getHardCodedRootColumn());
        return rootColumn.calcBestSplitClassification(membershipController, rowSampleWeights, targetPriors, targetColumn);
    } else {
        double bestGainValue = 0.0;
        final ColumnSample columnSample = colSamplingStrategy.getColumnSampleForTreeNode(treeNodeSignature);
        for (TreeAttributeColumnData col : columnSample) {
            if (forbiddenColumnSet.get(col.getMetaData().getAttributeIndex())) {
                continue;
            }
            SplitCandidate currentColSplit = col.calcBestSplitClassification(membershipController, rowSampleWeights, targetPriors, targetColumn);
            if (currentColSplit != null) {
                double gainValue = currentColSplit.getGainValue();
                if (gainValue > bestGainValue) {
                    bestGainValue = gainValue;
                    splitCandidate = currentColSplit;
                }
            }
        }
    }
    return splitCandidate;
}

Example 5 with TreeEnsembleLearnerConfiguration

use of org.knime.base.node.mine.treeensemble.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);
}