RMSE.java

/*
 * Apache License
 * Version 2.0, January 2004
 * http://www.apache.org/licenses/
 *
 *    Copyright 2013 Aurelian Tutuianu
 *    Copyright 2014 Aurelian Tutuianu
 *    Copyright 2015 Aurelian Tutuianu
 *    Copyright 2016 Aurelian Tutuianu
 *
 *    Licensed 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 rapaio.experiment.ml.eval;

import rapaio.data.VRange;
import rapaio.printer.Printable;
import rapaio.data.Frame;
import rapaio.data.Var;

import java.util.ArrayList;
import java.util.List;

import static rapaio.sys.WS.formatFlex;

/**
 * Regression evaluation tool which enables one to compute
 * Root Mean Squared Error, which is the sum of the squared
 * values of the residuals for all pairs of actual and
 * prediction variables.
 * <p>
 * User: Aurelian Tutuianu <paderati@yahoo.com>
 */
@Deprecated
public class RMSE implements Printable {

    private final List<String> targetNames;
    private final List<Var> actualVars;
    private final List<Var> predictVars;
    private double value;

    public RMSE(Frame actual, Frame predict, String... targetVarNames) {
        List<String> actualNames = VRange.of(targetVarNames).parseVarNames(actual);
        List<String> predictNames = VRange.of(targetVarNames).parseVarNames(predict);

        for (String varName : actualNames) {
            if (!predictNames.contains(varName)) {
                throw new IllegalArgumentException("actual and fit variables are not the same");
            }
        }
        for (String varName : predictNames) {
            if (!actualNames.contains(varName)) {
                throw new IllegalArgumentException("actual and fit variables are not the same");
            }
        }

        targetNames = actualNames;
        actualVars = new ArrayList<>();
        predictVars = new ArrayList<>();

        for (String targetName : targetNames) {
            actualVars.add(actual.var(targetName));
            predictVars.add(predict.var(targetName));
        }

        compute();
    }

    public RMSE(Var actual, Var predict) {
        targetNames = new ArrayList<>();
        targetNames.add(actual.name());

        actualVars = new ArrayList<>();
        predictVars = new ArrayList<>();

        actualVars.add(actual);
        predictVars.add(predict);

        compute();
    }

    private void compute() {
        double total = 0;
        double count = 0;

        for (int i = 0; i < targetNames.size(); i++) {
            for (int j = 0; j < actualVars.get(i).rowCount(); j++) {
                count++;
                total += Math.pow(actualVars.get(i).value(j) - predictVars.get(i).value(j), 2);
            }
        }
        value = Math.sqrt(total / count);
    }

    public double value() {
        return value;
    }

    @Override
    public String summary() {
        return "\n" +
                "> Root Mean Squared Error\n" +
                "RMSE: " + formatFlex(value) + "\n";
    }
}