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Apache Ignite® is a Distributed Database For High-Performance Computing With In-Memory Speed.

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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.apache.ignite.ml.optimization;

import org.apache.ignite.ml.math.Vector;
import org.apache.ignite.ml.math.functions.IgniteDifferentiableVectorToDoubleFunction;
import org.apache.ignite.ml.math.functions.IgniteFunction;

/**
 * Class containing popular loss functions.
 */
public class LossFunctions {
    /**
     * Mean squared error loss function.
     */
    public static IgniteFunction MSE = groundTruth ->
        new IgniteDifferentiableVectorToDoubleFunction() {
            /** {@inheritDoc} */
            @Override public Vector differential(Vector pnt) {
                double multiplier = 2.0 / pnt.size();
                return pnt.minus(groundTruth).times(multiplier);
            }

            /** {@inheritDoc} */
            @Override public Double apply(Vector vector) {
                return groundTruth.copy().map(vector, (a, b) -> {
                    double diff = a - b;
                    return diff * diff;
                }).sum() / (vector.size());
            }
        };
}