001/*
002 * Copyright (c) 2015-2020, Oracle and/or its affiliates. All rights reserved.
003 *
004 * Licensed under the Apache License, Version 2.0 (the "License");
005 * you may not use this file except in compliance with the License.
006 * You may obtain a copy of the License at
007 *
008 *     http://www.apache.org/licenses/LICENSE-2.0
009 *
010 * Unless required by applicable law or agreed to in writing, software
011 * distributed under the License is distributed on an "AS IS" BASIS,
012 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express implied.
013 * See the License for the specific language governing permissions and
014 * limitations under the License.
015 */
016
017package org.tribuo.regression.sgd.objectives;
018
019import com.oracle.labs.mlrg.olcut.provenance.ConfiguredObjectProvenance;
020import com.oracle.labs.mlrg.olcut.provenance.impl.ConfiguredObjectProvenanceImpl;
021import com.oracle.labs.mlrg.olcut.util.Pair;
022import org.tribuo.math.la.DenseVector;
023import org.tribuo.math.la.SGDVector;
024import org.tribuo.regression.sgd.RegressionObjective;
025
026/**
027 * Squared loss, i.e., l2.
028 */
029public class SquaredLoss implements RegressionObjective {
030
031    @Override
032    public Pair<Double, SGDVector> loss(DenseVector truth, SGDVector prediction) {
033        DenseVector difference = truth.subtract(prediction);
034        double loss = difference.reduce(0.0,(a) -> 0.5*a*a,Double::sum);
035        return new Pair<>(loss,difference);
036    }
037
038    @Override
039    public String toString() {
040        return "SquaredLoss";
041    }
042
043    @Override
044    public ConfiguredObjectProvenance getProvenance() {
045        return new ConfiguredObjectProvenanceImpl(this,"RegressionObjective");
046    }
047}