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jBPM Prediction based on SMILE addon

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/*
 * Licensed to the Apache Software Foundation (ASF) under one
 * or more contributor license agreements.  See the NOTICE file
 * distributed with this work for additional information
 * regarding copyright ownership.  The ASF licenses this file
 * to you 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.kogito.predictions.smile;

import java.util.HashMap;
import java.util.Map;

public class RandomForestConfiguration {

    private String outcomeName;
    private AttributeType outcomeType;
    private double confidenceThreshold;
    private int numTrees;
    private Map inputFeatures = new HashMap<>();

    public int getNumTrees() {
        return numTrees;
    }

    public void setNumTrees(int numTrees) {
        this.numTrees = numTrees;
    }

    /**
     * Returns the name of the output attribute
     *
     * @return The name of the output attribute
     */
    public String getOutcomeName() {
        return outcomeName;
    }

    public void setOutcomeName(String outcomeName) {
        this.outcomeName = outcomeName;
    }

    /**
     * Returns the type of the output attribute {@link AttributeType}
     *
     * @return The type of the output attribute
     */
    public AttributeType getOutcomeType() {
        return outcomeType;
    }

    public void setOutcomeType(AttributeType outcomeType) {
        this.outcomeType = outcomeType;
    }

    /**
     * Returns the confidence threshold to use for automatic task completion
     *
     * @return The confidence threshold, between 0.0 and 1.0
     */
    public double getConfidenceThreshold() {
        return confidenceThreshold;
    }

    public void setConfidenceThreshold(double confidenceThreshold) {
        this.confidenceThreshold = confidenceThreshold;
    }

    public Map getInputFeatures() {
        return inputFeatures;
    }

    public void setInputFeatures(Map inputFeatures) {
        this.inputFeatures = inputFeatures;
    }
}