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Example 6 with TreeNodeSignatureFactory

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

the class RegressionTreeLearnerNodeModel method execute.

/**
 * {@inheritDoc}
 */
@Override
protected PortObject[] execute(final PortObject[] inObjects, final ExecutionContext exec) throws Exception {
    BufferedDataTable t = (BufferedDataTable) inObjects[0];
    DataTableSpec spec = t.getDataTableSpec();
    final FilterLearnColumnRearranger learnRearranger = m_configuration.filterLearnColumns(spec);
    String warn = learnRearranger.getWarning();
    BufferedDataTable learnTable = exec.createColumnRearrangeTable(t, learnRearranger, exec.createSubProgress(0.0));
    DataTableSpec learnSpec = learnTable.getDataTableSpec();
    ExecutionMonitor readInExec = exec.createSubProgress(0.1);
    ExecutionMonitor learnExec = exec.createSubProgress(0.9);
    TreeDataCreator dataCreator = new TreeDataCreator(m_configuration, learnSpec, learnTable.getRowCount());
    exec.setProgress("Reading data into memory");
    TreeData data = dataCreator.readData(learnTable, m_configuration, readInExec);
    m_hiliteRowSample = dataCreator.getDataRowsForHilite();
    m_viewMessage = dataCreator.getViewMessage();
    String dataCreationWarning = dataCreator.getAndClearWarningMessage();
    if (dataCreationWarning != null) {
        if (warn == null) {
            warn = dataCreationWarning;
        } else {
            warn = warn + "\n" + dataCreationWarning;
        }
    }
    readInExec.setProgress(1.0);
    exec.setMessage("Learning tree");
    RandomData rd = m_configuration.createRandomData();
    final IDataIndexManager indexManager;
    if (data.getTreeType() == TreeType.BitVector) {
        indexManager = new BitVectorDataIndexManager(data.getNrRows());
    } else {
        indexManager = new DefaultDataIndexManager(data);
    }
    TreeNodeSignatureFactory signatureFactory = null;
    int maxLevels = m_configuration.getMaxLevels();
    if (maxLevels < TreeEnsembleLearnerConfiguration.MAX_LEVEL_INFINITE) {
        int capacity = IntMath.pow(2, maxLevels - 1);
        signatureFactory = new TreeNodeSignatureFactory(capacity);
    } else {
        signatureFactory = new TreeNodeSignatureFactory();
    }
    final RowSample rowSample = m_configuration.createRowSampler(data).createRowSample(rd);
    TreeLearnerRegression treeLearner = new TreeLearnerRegression(m_configuration, data, indexManager, signatureFactory, rd, rowSample);
    TreeModelRegression regTree = treeLearner.learnSingleTree(learnExec, rd);
    RegressionTreeModel model = new RegressionTreeModel(m_configuration, data.getMetaData(), regTree, data.getTreeType());
    RegressionTreeModelPortObjectSpec treePortObjectSpec = new RegressionTreeModelPortObjectSpec(learnSpec);
    RegressionTreeModelPortObject treePortObject = new RegressionTreeModelPortObject(model, treePortObjectSpec);
    learnExec.setProgress(1.0);
    m_treeModelPortObject = treePortObject;
    if (warn != null) {
        setWarningMessage(warn);
    }
    return new PortObject[] { treePortObject };
}
Also used : RegressionTreeModelPortObject(org.knime.base.node.mine.treeensemble2.model.RegressionTreeModelPortObject) DataTableSpec(org.knime.core.data.DataTableSpec) RandomData(org.apache.commons.math.random.RandomData) RegressionTreeModel(org.knime.base.node.mine.treeensemble2.model.RegressionTreeModel) IDataIndexManager(org.knime.base.node.mine.treeensemble2.data.memberships.IDataIndexManager) BitVectorDataIndexManager(org.knime.base.node.mine.treeensemble2.data.memberships.BitVectorDataIndexManager) RegressionTreeModelPortObjectSpec(org.knime.base.node.mine.treeensemble2.model.RegressionTreeModelPortObjectSpec) DefaultDataIndexManager(org.knime.base.node.mine.treeensemble2.data.memberships.DefaultDataIndexManager) TreeModelRegression(org.knime.base.node.mine.treeensemble2.model.TreeModelRegression) BufferedDataTable(org.knime.core.node.BufferedDataTable) FilterLearnColumnRearranger(org.knime.base.node.mine.treeensemble2.node.learner.TreeEnsembleLearnerConfiguration.FilterLearnColumnRearranger) TreeData(org.knime.base.node.mine.treeensemble2.data.TreeData) TreeLearnerRegression(org.knime.base.node.mine.treeensemble2.learner.TreeLearnerRegression) RowSample(org.knime.base.node.mine.treeensemble2.sample.row.RowSample) ExecutionMonitor(org.knime.core.node.ExecutionMonitor) TreeDataCreator(org.knime.base.node.mine.treeensemble2.data.TreeDataCreator) RegressionTreeModelPortObject(org.knime.base.node.mine.treeensemble2.model.RegressionTreeModelPortObject) PortObject(org.knime.core.node.port.PortObject) TreeNodeSignatureFactory(org.knime.base.node.mine.treeensemble2.learner.TreeNodeSignatureFactory)

Aggregations

TreeNodeSignatureFactory (org.knime.base.node.mine.treeensemble2.learner.TreeNodeSignatureFactory)6 TreeNodeSignature (org.knime.base.node.mine.treeensemble2.model.TreeNodeSignature)5 RandomData (org.apache.commons.math.random.RandomData)3 Test (org.junit.Test)3 TreeData (org.knime.base.node.mine.treeensemble2.data.TreeData)3 TreeModelRegression (org.knime.base.node.mine.treeensemble2.model.TreeModelRegression)3 ArrayList (java.util.ArrayList)2 HashMap (java.util.HashMap)2 Map (java.util.Map)2 TreeLearnerRegression (org.knime.base.node.mine.treeensemble2.learner.TreeLearnerRegression)2 RowSample (org.knime.base.node.mine.treeensemble2.sample.row.RowSample)2 ExecutionMonitor (org.knime.core.node.ExecutionMonitor)2 Future (java.util.concurrent.Future)1 Semaphore (java.util.concurrent.Semaphore)1 AtomicReference (java.util.concurrent.atomic.AtomicReference)1 NominalValueRepresentation (org.knime.base.node.mine.treeensemble2.data.NominalValueRepresentation)1 TreeDataCreator (org.knime.base.node.mine.treeensemble2.data.TreeDataCreator)1 TreeTargetNominalColumnData (org.knime.base.node.mine.treeensemble2.data.TreeTargetNominalColumnData)1 TreeTargetNumericColumnData (org.knime.base.node.mine.treeensemble2.data.TreeTargetNumericColumnData)1 BitVectorDataIndexManager (org.knime.base.node.mine.treeensemble2.data.memberships.BitVectorDataIndexManager)1