Examples with PMMLRegressionTranslator org.knime.base.node.mine.regression.PMMLRegressionTranslator used on opensource projects

Example 1 with PMMLRegressionTranslator

use of org.knime.base.node.mine.regression.PMMLRegressionTranslator in project knime-core by knime.

the class PolyRegLearnerNodeModel method createPMMLModel.

private PMMLPortObject createPMMLModel(final PMMLPortObject inPMMLPort, final DataTableSpec inSpec) throws InvalidSettingsException, SAXException {
    NumericPredictor[] preds = new NumericPredictor[m_betas.length - 1];
    int deg = m_settings.getDegree();
    for (int i = 0; i < m_columnNames.length; i++) {
        for (int k = 0; k < deg; k++) {
            preds[i * deg + k] = new NumericPredictor(m_columnNames[i], k + 1, m_betas[i * deg + k + 1]);
        }
    }
    RegressionTable tab = new RegressionTable(m_betas[0], preds);
    PMMLPortObjectSpec pmmlSpec = null;
    if (inPMMLPort != null) {
        pmmlSpec = inPMMLPort.getSpec();
    }
    PMMLPortObjectSpec spec = createModelSpec(pmmlSpec, inSpec);
    /* To maintain compatibility with the previous SAX-based implementation.
         * */
    String targetField = "Response";
    List<String> targetFields = spec.getTargetFields();
    if (!targetFields.isEmpty()) {
        targetField = targetFields.get(0);
    }
    PMMLPortObject outPMMLPort = new PMMLPortObject(spec, inPMMLPort, inSpec);
    PMMLRegressionTranslator trans = new PMMLRegressionTranslator("KNIME Polynomial Regression", "PolynomialRegression", tab, targetField);
    outPMMLPort.addModelTranslater(trans);
    return outPMMLPort;
}

Example 2 with PMMLRegressionTranslator

use of org.knime.base.node.mine.regression.PMMLRegressionTranslator in project knime-core by knime.

the class RegressionPredictorNodeModel method execute.

/**
 * {@inheritDoc}
 */
@Override
public PortObject[] execute(final PortObject[] inData, final ExecutionContext exec) throws Exception {
    PMMLPortObject regModel = (PMMLPortObject) inData[0];
    List<Node> models = regModel.getPMMLValue().getModels(PMMLModelType.RegressionModel);
    if (models.isEmpty()) {
        String msg = "No Regression Model found.";
        LOGGER.error(msg);
        throw new RuntimeException(msg);
    }
    PMMLRegressionTranslator trans = new PMMLRegressionTranslator();
    regModel.initializeModelTranslator(trans);
    BufferedDataTable data = (BufferedDataTable) inData[1];
    DataTableSpec spec = data.getDataTableSpec();
    ColumnRearranger c = createRearranger(spec, regModel.getSpec(), trans);
    BufferedDataTable out = exec.createColumnRearrangeTable(data, c, exec);
    return new BufferedDataTable[] { out };
}

Example 3 with PMMLRegressionTranslator

use of org.knime.base.node.mine.regression.PMMLRegressionTranslator in project knime-core by knime.

the class PolyRegLearnerNodeModel method createPMMLModel.

private PMMLPortObject createPMMLModel(final PMMLPortObject inPMMLPort, final DataTableSpec inSpec) throws InvalidSettingsException, SAXException {
    NumericPredictor[] preds = new NumericPredictor[m_betas.length - 1];
    int deg = m_settings.getDegree();
    for (int i = 0; i < m_columnNames.length; i++) {
        for (int k = 0; k < deg; k++) {
            preds[i * deg + k] = new NumericPredictor(m_columnNames[i], k + 1, m_betas[i * deg + k + 1]);
        }
    }
    RegressionTable tab = new RegressionTable(m_betas[0], preds);
    PMMLPortObjectSpec pmmlSpec = null;
    if (inPMMLPort != null) {
        pmmlSpec = inPMMLPort.getSpec();
    }
    PMMLPortObjectSpec spec = createModelSpec(pmmlSpec, inSpec);
    /* To maintain compatibility with the previous SAX-based implementation.
         * */
    String targetField = "Response";
    List<String> targetFields = spec.getTargetFields();
    if (!targetFields.isEmpty()) {
        targetField = targetFields.get(0);
    }
    PMMLPortObject outPMMLPort = new PMMLPortObject(spec, inPMMLPort, inSpec);
    PMMLRegressionTranslator trans = new PMMLRegressionTranslator("KNIME Polynomial Regression", "PolynomialRegression", tab, targetField);
    outPMMLPort.addModelTranslater(trans);
    return outPMMLPort;
}

Example 4 with PMMLRegressionTranslator

use of org.knime.base.node.mine.regression.PMMLRegressionTranslator in project knime-core by knime.

the class LinearRegressionContent method createPortObject.

/**
 * Creates a new PMML regression port object from this linear regression
 * model.
 * @param inPMMLPort the incoming PMMLPort object (can be null)
 * @param dts the full data table spec with which the regression
 *      model was created.
 * @param learningSpec a data table spec containing only learning columns
 * @return a port object
 * @throws InvalidSettingsException if the settings are invalid
 */
public PMMLPortObject createPortObject(final PMMLPortObject inPMMLPort, final DataTableSpec dts, final DataTableSpec learningSpec) throws InvalidSettingsException {
    PMMLPortObjectSpec inPMMLSpec = null;
    if (inPMMLPort != null) {
        inPMMLSpec = inPMMLPort.getSpec();
    }
    PMMLPortObjectSpec spec = createPortObjectSpec(inPMMLSpec, dts, learningSpec);
    PMMLPortObject outPMMLPort = new PMMLPortObject(spec, inPMMLPort);
    NumericPredictor[] nps = new NumericPredictor[m_multipliers.length];
    for (int i = 0; i < nps.length; i++) {
        nps[i] = new NumericPredictor(m_spec.getColumnSpec(i).getName(), 1, m_multipliers[i]);
    }
    RegressionTable regressionTable = new RegressionTable(m_offset, nps);
    /* To maintain compatibility with the previous SAX-based implementation.
         * */
    String targetField = "Response";
    List<String> targetFields = spec.getTargetFields();
    if (!targetFields.isEmpty()) {
        targetField = targetFields.get(0);
    }
    PMMLRegressionTranslator trans = new PMMLRegressionTranslator(MODEL_NAME, ALGORITHM_NAME, regressionTable, targetField);
    outPMMLPort.addModelTranslater(trans);
    return outPMMLPort;
}