/**
* Copyright (C) 2001-2017 by RapidMiner and the contributors
*
* Complete list of developers available at our web site:
*
* http://rapidminer.com
*
* This program is free software: you can redistribute it and/or modify it under the terms of the
* GNU Affero General Public License as published by the Free Software Foundation, either version 3
* of the License, or (at your option) any later version.
*
* This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without
* even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
* Affero General Public License for more details.
*
* You should have received a copy of the GNU Affero General Public License along with this program.
* If not, see http://www.gnu.org/licenses/.
*/
package com.rapidminer.operator.learner.functions.linear;
import com.rapidminer.example.ExampleSet;
import com.rapidminer.parameter.ParameterType;
import com.rapidminer.parameter.UndefinedParameterError;
import java.util.Collections;
import java.util.List;
/**
* This method just does not perform any feature selection methods.
*
* @author Sebastian Land
*/
public class PlainLinearRegressionMethod implements LinearRegressionMethod {
@Override
public LinearRegressionResult applyMethod(LinearRegression regression, boolean useBias, double ridge,
ExampleSet exampleSet, boolean[] isUsedAttribute, int numberOfExamples, int numberOfUsedAttributes,
double[] means, double labelMean, double[] standardDeviations, double labelStandardDeviation,
double[] coefficientsOnFullData, double errorOnFullData) throws UndefinedParameterError {
LinearRegressionResult result = new LinearRegressionResult();
result.coefficients = coefficientsOnFullData;
result.error = errorOnFullData;
result.isUsedAttribute = isUsedAttribute;
return result;
}
@Override
public List<ParameterType> getParameterTypes() {
return Collections.emptyList();
}
}