package org.apache.samoa.moa.classifiers.core.driftdetection; /* * #%L * SAMOA * %% * Copyright (C) 2014 - 2015 Apache Software Foundation * %% * 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. * #L% */ import org.apache.samoa.moa.core.ObjectRepository; import org.apache.samoa.moa.tasks.TaskMonitor; import com.github.javacliparser.FloatOption; import com.github.javacliparser.IntOption; /** * Drift detection method based in Geometric Moving Average Test * * * @author Manuel Baena (mbaena@lcc.uma.es) * @version $Revision: 7 $ */ public class GeometricMovingAverageDM extends AbstractChangeDetector { private static final long serialVersionUID = -3518369648142099719L; public IntOption minNumInstancesOption = new IntOption( "minNumInstances", 'n', "The minimum number of instances before permitting detecting change.", 30, 0, Integer.MAX_VALUE); public FloatOption lambdaOption = new FloatOption("lambda", 'l', "Threshold parameter of the Geometric Moving Average Test", 1, 0.0, Float.MAX_VALUE); public FloatOption alphaOption = new FloatOption("alpha", 'a', "Alpha parameter of the Geometric Moving Average Test", .99, 0.0, 1.0); private double m_n; private double sum; private double x_mean; private double alpha; private double lambda; public GeometricMovingAverageDM() { resetLearning(); } @Override public void resetLearning() { m_n = 1.0; x_mean = 0.0; sum = 0.0; alpha = this.alphaOption.getValue(); lambda = this.lambdaOption.getValue(); } @Override public void input(double x) { // It monitors the error rate if (this.isChangeDetected) { resetLearning(); } x_mean = x_mean + (x - x_mean) / m_n; sum = alpha * sum + (1.0 - alpha) * (x - x_mean); m_n++; this.estimation = x_mean; this.isChangeDetected = false; this.isWarningZone = false; this.delay = 0; if (m_n < this.minNumInstancesOption.getValue()) { return; } if (sum > this.lambda) { this.isChangeDetected = true; } } @Override public void getDescription(StringBuilder sb, int indent) { // TODO Auto-generated method stub } @Override protected void prepareForUseImpl(TaskMonitor monitor, ObjectRepository repository) { // TODO Auto-generated method stub } }