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/*
 * Copyright 2020 Red Hat, Inc. and/or its affiliates.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
package  org.kie.pmml.models.tree.model;

import java.util.Collections;
import java.util.Map;
import java.util.function.Function;

import org.kie.pmml.api.runtime.PMMLRuntimeContext;
import org.kie.pmml.commons.model.KiePMMLModel;

public abstract class KiePMMLTreeModel extends KiePMMLModel {

    private static final long serialVersionUID = -5158590062736070465L;

    protected Function, KiePMMLNodeResult> nodeFunction;

    protected KiePMMLTreeModel(String fileName, String modelName) {
        super(fileName, modelName, Collections.emptyList());
    }

    @Override
    public Object evaluate(final Map requestData,
                           final PMMLRuntimeContext context) {
        KiePMMLNodeResult kiePMMLNodeResult = nodeFunction.apply(requestData);
        context.setProbabilityResultMap(kiePMMLNodeResult.getProbabilityMap());
        return kiePMMLNodeResult.getScore();
    }

}




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