Examples with RegressionTreeModelPortObjectSpec org.knime.base.node.mine.treeensemble2.model.RegressionTreeModelPortObjectSpec used on opensource projects

Example 11 with RegressionTreeModelPortObjectSpec

use of org.knime.base.node.mine.treeensemble2.model.RegressionTreeModelPortObjectSpec in project knime-core by knime.

the class RegressionTreePredictorNodeModel method execute.

/**
 * {@inheritDoc}
 */
@Override
protected PortObject[] execute(final PortObject[] inObjects, final ExecutionContext exec) throws Exception {
    RegressionTreeModelPortObject model = (RegressionTreeModelPortObject) inObjects[0];
    RegressionTreeModelPortObjectSpec modelSpec = model.getSpec();
    BufferedDataTable data = (BufferedDataTable) inObjects[1];
    DataTableSpec dataSpec = data.getDataTableSpec();
    final RegressionTreePredictor pred = new RegressionTreePredictor(model.getModel(), modelSpec, dataSpec, m_configuration);
    ColumnRearranger rearranger = pred.getPredictionRearranger();
    BufferedDataTable outTable = exec.createColumnRearrangeTable(data, rearranger, exec);
    return new BufferedDataTable[] { outTable };
}

Example 12 with RegressionTreeModelPortObjectSpec

use of org.knime.base.node.mine.treeensemble2.model.RegressionTreeModelPortObjectSpec in project knime-core by knime.

the class RegressionTreePredictorNodeModel method configure.

/**
 * {@inheritDoc}
 */
@Override
protected PortObjectSpec[] configure(final PortObjectSpec[] inSpecs) throws InvalidSettingsException {
    RegressionTreeModelPortObjectSpec modelSpec = (RegressionTreeModelPortObjectSpec) inSpecs[0];
    String targetColName = modelSpec.getTargetColumn().getName();
    if (m_configuration == null) {
        m_configuration = RegressionTreePredictorConfiguration.createDefault(targetColName);
    } else if (!m_configuration.isChangePredictionColumnName()) {
        m_configuration.setPredictionColumnName(RegressionTreePredictorConfiguration.getPredictColumnName(targetColName));
    }
    DataTableSpec dataSpec = (DataTableSpec) inSpecs[1];
    final RegressionTreePredictor pred = new RegressionTreePredictor(null, modelSpec, dataSpec, m_configuration);
    ColumnRearranger rearranger = pred.getPredictionRearranger();
    // rearranger may be null if confidence values are appended but the
    // model does not have a list of possible target values
    DataTableSpec outSpec = rearranger != null ? rearranger.createSpec() : null;
    return new DataTableSpec[] { outSpec };
}