/*
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 *  * This program and the accompanying materials are made available under the
 *  * terms of the Apache License, Version 2.0 which is available at
 *  * https://www.apache.org/licenses/LICENSE-2.0.
 *  *
 *  *  See the NOTICE file distributed with this work for additional
 *  *  information regarding copyright ownership.
 *  * 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
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package org.deeplearning4j.earlystopping.scorecalc;

import org.deeplearning4j.earlystopping.scorecalc.base.BaseIEvaluationScoreCalculator;
import org.deeplearning4j.nn.api.Model;
import org.nd4j.evaluation.regression.RegressionEvaluation;
import org.nd4j.evaluation.regression.RegressionEvaluation.Metric;
import org.nd4j.linalg.dataset.api.iterator.DataSetIterator;

public class RegressionScoreCalculator extends BaseIEvaluationScoreCalculator<Model, RegressionEvaluation> {

    protected final Metric metric;

    public RegressionScoreCalculator(Metric metric, DataSetIterator iterator){
        super(iterator);
        this.metric = metric;
    }

    @Override
    protected RegressionEvaluation newEval() {
        return new RegressionEvaluation();
    }

    @Override
    protected double finalScore(RegressionEvaluation eval) {
        return eval.scoreForMetric(metric);
    }

    @Override
    public boolean minimizeScore() {
        return metric.minimize();
    }
}
