moa.classifiers.rules.multilabel.errormeasurers.RelativeMeanAbsoluteDeviationMT Maven / Gradle / Ivy

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/*
 *    RelativeMeanAbsoluteDeviationMT.java
 *    Copyright (C) 2017 University of Porto, Portugal
 *    @author J. Duarte, J. Gama
 *
 *    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 moa.classifiers.rules.multilabel.errormeasurers;

import com.yahoo.labs.samoa.instances.Prediction;


/**
 * Relative Mean Absolute Deviation for multitarget and with fading factor
 */


public class RelativeMeanAbsoluteDeviationMT extends AbstractMultiTargetErrorMeasurer {

	/**
	 * 
	 */
	protected double weightSeen;
	protected double [] sumError;
	
	protected double [] sumY;
	protected double [] sumErrorToTargetMean;
	
	private static final long serialVersionUID = 1L;
	protected boolean hasStarted;
	protected int numLearnedOutputs;

	@Override
	public void addPrediction(Prediction prediction, Prediction trueClass, double weight) {
		int numOutputs=prediction.numOutputAttributes();
		if (!hasStarted){
			sumError=new double[numOutputs];
			sumY=new double[numOutputs];
			sumErrorToTargetMean=new double[numOutputs];
			hasStarted=true;
			for(int i=0; i