moa.classifiers.rules.multilabel.outputselectors.StdDevThreshold Maven / Gradle / Ivy

Go to download

Show more of this group Show more artifacts with this name
Show all versions of moa Show documentation

Massive On-line Analysis is an environment for massive data mining. MOA provides a framework for data stream mining and includes tools for evaluation and a collection of machine learning algorithms. Related to the WEKA project, also written in Java, while scaling to more demanding problems.

The newest version!

/*
 *    StdDevThreshold.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.outputselectors;

import java.util.LinkedList;

import moa.classifiers.rules.core.Utils;
import moa.core.DoubleVector;
import moa.core.ObjectRepository;
import moa.options.AbstractOptionHandler;
import moa.tasks.TaskMonitor;

import com.github.javacliparser.FloatOption;

public class StdDevThreshold extends AbstractOptionHandler implements
OutputAttributesSelector {

	/**
	 * 
	 */
	private static final long serialVersionUID = 1L;

	public FloatOption thresholdOption = new FloatOption("Threshold",
			'p', "Maximum allowed standar deviation ratio (stdev(new)/stdev(old)).",
			1.0, 0.5, 2.0);


	public int[] getNextOutputIndices(DoubleVector[] resultingStatistics, DoubleVector[] currentLiteralStatistics, int[] currentIndices) {
		int numCurrentOutputs=resultingStatistics.length;
		double threshold=thresholdOption.getValue();
		//get new outputs
		LinkedList newOutputsList= new LinkedList();
		for(int i=0; i