Examples with TreeModel org.dmg.pmml.tree.TreeModel used on opensource projects

Example 46 with TreeModel

use of org.dmg.pmml.tree.TreeModel in project jpmml-r by jpmml.

the class RangerConverter method encodeRegression.

private MiningModel encodeRegression(RGenericVector forest, Schema schema) {
    ScoreEncoder scoreEncoder = new ScoreEncoder() {

        @Override
        public Node encode(Node node, Number splitValue, RNumberVector<?> terminalClassCount) {
            node.setScore(splitValue);
            return node;
        }
    };
    List<TreeModel> treeModels = encodeForest(forest, MiningFunction.REGRESSION, scoreEncoder, schema);
    MiningModel miningModel = new MiningModel(MiningFunction.REGRESSION, ModelUtil.createMiningSchema(schema.getLabel())).setSegmentation(MiningModelUtil.createSegmentation(Segmentation.MultipleModelMethod.AVERAGE, treeModels));
    return miningModel;
}

Example 47 with TreeModel

use of org.dmg.pmml.tree.TreeModel in project jpmml-r by jpmml.

the class BoostingConverter method encodeModel.

@Override
public Model encodeModel(Schema schema) {
    RGenericVector boosting = getObject();
    RGenericVector trees = boosting.getGenericElement("trees");
    RDoubleVector weights = boosting.getDoubleElement("weights");
    CategoricalLabel categoricalLabel = (CategoricalLabel) schema.getLabel();
    List<TreeModel> treeModels = encodeTreeModels(trees);
    MiningModel miningModel = new MiningModel(MiningFunction.CLASSIFICATION, ModelUtil.createMiningSchema(categoricalLabel)).setSegmentation(MiningModelUtil.createSegmentation(Segmentation.MultipleModelMethod.WEIGHTED_MAJORITY_VOTE, treeModels, weights.getValues())).setOutput(ModelUtil.createProbabilityOutput(DataType.DOUBLE, categoricalLabel));
    return miningModel;
}

Example 48 with TreeModel

use of org.dmg.pmml.tree.TreeModel in project jpmml-r by jpmml.

the class BinaryTreeConverter method encodeTreeModel.

private TreeModel encodeTreeModel(RGenericVector tree, Schema schema) {
    Node root = encodeNode(tree, True.INSTANCE, schema);
    TreeModel treeModel = new TreeModel(this.miningFunction, ModelUtil.createMiningSchema(schema.getLabel()), root).setSplitCharacteristic(TreeModel.SplitCharacteristic.BINARY_SPLIT);
    return treeModel;
}