cavis/cavis-dnn/cavis-dnn-nn/src/main/java/org/deeplearning4j/earlystopping/scorecalc/ClassificationScoreCalculator.java

/*
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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
 *  * License for the specific language governing permissions and limitations
 *  * under the License.
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 *  * SPDX-License-Identifier: Apache-2.0
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package org.deeplearning4j.earlystopping.scorecalc;

import net.brutex.ai.dnn.api.IModel;
import org.deeplearning4j.earlystopping.scorecalc.base.BaseIEvaluationScoreCalculator;
import org.nd4j.evaluation.classification.Evaluation;
import org.nd4j.linalg.dataset.api.iterator.DataSetIterator;
import org.nd4j.linalg.dataset.api.iterator.MultiDataSetIterator;

public class ClassificationScoreCalculator extends BaseIEvaluationScoreCalculator<IModel, Evaluation> {

    protected final Evaluation.Metric metric;

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

    public ClassificationScoreCalculator(Evaluation.Metric metric, MultiDataSetIterator iterator){
        super(iterator);
        this.metric = metric;
    }

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

    @Override
    protected double finalScore(Evaluation e) {
        return e.scoreForMetric(metric);
    }

    @Override
    public boolean minimizeScore() {
        //All classification metrics should be maximized: ACCURACY, F1, PRECISION, RECALL, GMEASURE, MCC
        return false;
    }
}