Examples with Schema org.jpmml.converter.Schema used on opensource projects

Example 11 with Schema

use of org.jpmml.converter.Schema in project jpmml-r by jpmml.

the class ModelConverter method encodePMML.

public PMML encodePMML(RExpEncoder encoder) {
    encodeSchema(encoder);
    Schema schema = encoder.createSchema();
    Model model = encodeModel(schema);
    PMML pmml = encoder.encodePMML(model);
    return pmml;
}

Example 12 with Schema

use of org.jpmml.converter.Schema in project jpmml-sparkml by jpmml.

the class TreeModelUtil method encodeDecisionTreeEnsemble.

public static <M extends Model<M> & TreeEnsembleModel<T>, T extends Model<T> & DecisionTreeModel> List<TreeModel> encodeDecisionTreeEnsemble(M model, PredicateManager predicateManager, Schema schema) {
    Schema segmentSchema = schema.toAnonymousSchema();
    List<TreeModel> treeModels = new ArrayList<>();
    T[] trees = model.trees();
    for (T tree : trees) {
        TreeModel treeModel = encodeDecisionTree(tree, predicateManager, segmentSchema);
        treeModels.add(treeModel);
    }
    return treeModels;
}

Example 13 with Schema

use of org.jpmml.converter.Schema in project jpmml-sparkml by jpmml.

the class ConverterUtil method toPMML.

public static PMML toPMML(StructType schema, PipelineModel pipelineModel) {
    checkVersion();
    SparkMLEncoder encoder = new SparkMLEncoder(schema);
    List<org.dmg.pmml.Model> models = new ArrayList<>();
    Iterable<Transformer> transformers = getTransformers(pipelineModel);
    for (Transformer transformer : transformers) {
        TransformerConverter<?> converter = ConverterUtil.createConverter(transformer);
        if (converter instanceof FeatureConverter) {
            FeatureConverter<?> featureConverter = (FeatureConverter<?>) converter;
            featureConverter.registerFeatures(encoder);
        } else if (converter instanceof ModelConverter) {
            ModelConverter<?> modelConverter = (ModelConverter<?>) converter;
            org.dmg.pmml.Model model = modelConverter.registerModel(encoder);
            models.add(model);
        } else {
            throw new IllegalArgumentException("Expected a " + FeatureConverter.class.getName() + " or " + ModelConverter.class.getName() + " instance, got " + converter);
        }
    }
    org.dmg.pmml.Model rootModel;
    if (models.size() == 1) {
        rootModel = Iterables.getOnlyElement(models);
    } else if (models.size() > 1) {
        List<MiningField> targetMiningFields = new ArrayList<>();
        for (org.dmg.pmml.Model model : models) {
            MiningSchema miningSchema = model.getMiningSchema();
            List<MiningField> miningFields = miningSchema.getMiningFields();
            for (MiningField miningField : miningFields) {
                MiningField.UsageType usageType = miningField.getUsageType();
                switch(usageType) {
                    case PREDICTED:
                    case TARGET:
                        targetMiningFields.add(miningField);
                        break;
                    default:
                        break;
                }
            }
        }
        MiningSchema miningSchema = new MiningSchema(targetMiningFields);
        MiningModel miningModel = MiningModelUtil.createModelChain(models, new Schema(null, Collections.<Feature>emptyList())).setMiningSchema(miningSchema);
        rootModel = miningModel;
    } else {
        throw new IllegalArgumentException("Expected a pipeline with one or more models, got a pipeline with zero models");
    }
    PMML pmml = encoder.encodePMML(rootModel);
    return pmml;
}

Example 14 with Schema

use of org.jpmml.converter.Schema in project jpmml-sparkml by jpmml.

the class ModelConverter method registerModel.

public org.dmg.pmml.Model registerModel(SparkMLEncoder encoder) {
    Schema schema = encodeSchema(encoder);
    Label label = schema.getLabel();
    org.dmg.pmml.Model model = encodeModel(schema);
    List<OutputField> sparkOutputFields = registerOutputFields(label, encoder);
    if (sparkOutputFields != null && sparkOutputFields.size() > 0) {
        org.dmg.pmml.Model lastModel = getLastModel(model);
        Output output = lastModel.getOutput();
        if (output == null) {
            output = new Output();
            lastModel.setOutput(output);
        }
        List<OutputField> outputFields = output.getOutputFields();
        outputFields.addAll(0, sparkOutputFields);
    }
    return model;
}

Example 15 with Schema

use of org.jpmml.converter.Schema in project jpmml-sparkml by jpmml.

the class GBTClassificationModelConverter method encodeModel.

@Override
public MiningModel encodeModel(Schema schema) {
    GBTClassificationModel model = getTransformer();
    String lossType = model.getLossType();
    switch(lossType) {
        case "logistic":
            break;
        default:
            throw new IllegalArgumentException("Loss function " + lossType + " is not supported");
    }
    Schema segmentSchema = new Schema(new ContinuousLabel(null, DataType.DOUBLE), schema.getFeatures());
    List<TreeModel> treeModels = TreeModelUtil.encodeDecisionTreeEnsemble(model, segmentSchema);
    MiningModel miningModel = new MiningModel(MiningFunction.REGRESSION, ModelUtil.createMiningSchema(segmentSchema.getLabel())).setSegmentation(MiningModelUtil.createSegmentation(Segmentation.MultipleModelMethod.WEIGHTED_SUM, treeModels, Doubles.asList(model.treeWeights()))).setOutput(ModelUtil.createPredictedOutput(FieldName.create("gbtValue"), OpType.CONTINUOUS, DataType.DOUBLE));
    return MiningModelUtil.createBinaryLogisticClassification(miningModel, 2d, 0d, RegressionModel.NormalizationMethod.LOGIT, false, schema);
}