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

Example 11 with MultiClassGradientBoostedTreesModel

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

the class LKGradientBoostingPredictorCellFactory method createFactory.

public static LKGradientBoostingPredictorCellFactory createFactory(final GradientBoostingPredictor<MultiClassGradientBoostedTreesModel> predictor) throws InvalidSettingsException {
    TreeEnsemblePredictorConfiguration config = predictor.getConfiguration();
    DataTableSpec testSpec = predictor.getDataSpec();
    TreeEnsembleModelPortObjectSpec modelSpec = predictor.getModelSpec();
    ArrayList<DataColumnSpec> newColSpecs = new ArrayList<DataColumnSpec>();
    UniqueNameGenerator nameGen = new UniqueNameGenerator(testSpec);
    newColSpecs.add(nameGen.newColumn(config.getPredictionColumnName(), StringCell.TYPE));
    if (config.isAppendPredictionConfidence()) {
        newColSpecs.add(nameGen.newColumn("Confidence", DoubleCell.TYPE));
    }
    if (config.isAppendClassConfidences()) {
        final String targetColName = modelSpec.getTargetColumn().getName();
        final String suffix = config.getSuffixForClassProbabilities();
        for (String val : modelSpec.getTargetColumnPossibleValueMap().keySet()) {
            String colName = "P(" + targetColName + "=" + val + ")" + suffix;
            newColSpecs.add(nameGen.newColumn(colName, DoubleCell.TYPE));
        }
    }
    final Map<String, DataCell> targetValueMap = modelSpec.getTargetColumnPossibleValueMap();
    return new LKGradientBoostingPredictorCellFactory(newColSpecs.toArray(new DataColumnSpec[newColSpecs.size()]), predictor.getModel(), modelSpec.getLearnTableSpec(), modelSpec.calculateFilterIndices(testSpec), config, targetValueMap);
}