com.rapidminer.operator.preprocessing.weighting.EqualLabelWeighting.java Source code

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Here is the source code for com.rapidminer.operator.preprocessing.weighting.EqualLabelWeighting.java

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/**
 * 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.preprocessing.weighting;

import java.util.HashMap;
import java.util.List;
import java.util.Map;

import org.apache.commons.lang.ArrayUtils;

import com.rapidminer.example.Attribute;
import com.rapidminer.example.Attributes;
import com.rapidminer.example.Example;
import com.rapidminer.example.ExampleSet;
import com.rapidminer.example.Statistics;
import com.rapidminer.example.table.AttributeFactory;
import com.rapidminer.example.table.NominalMapping;
import com.rapidminer.operator.OperatorDescription;
import com.rapidminer.operator.OperatorException;
import com.rapidminer.operator.OperatorVersion;
import com.rapidminer.operator.annotation.ResourceConsumptionEstimator;
import com.rapidminer.operator.ports.metadata.SetRelation;
import com.rapidminer.parameter.ParameterType;
import com.rapidminer.parameter.ParameterTypeDouble;
import com.rapidminer.parameter.UndefinedParameterError;
import com.rapidminer.tools.Ontology;
import com.rapidminer.tools.OperatorResourceConsumptionHandler;
import com.rapidminer.tools.math.container.Range;

/**
 * This operator distributes example weights so that all example weights of labels sum up equally.
 *
 * @author Sebastian Land
 */
public class EqualLabelWeighting extends AbstractExampleWeighting {

    private static final String PARAMETER_TOTAL_WEIGHT = "total_weight";

    /**
     * Incompatible version, old version writes into the exampleset, if original output port is not
     * connected.
     */
    private static final OperatorVersion VERSION_MAY_WRITE_INTO_DATA = new OperatorVersion(7, 1, 1);

    public EqualLabelWeighting(OperatorDescription description) {
        super(description);
    }

    @Override
    protected Range getWeightAttributeRange() {
        try {
            return new Range(0, getParameterAsDouble(PARAMETER_TOTAL_WEIGHT));
        } catch (UndefinedParameterError e) {
            return new Range(0, Double.POSITIVE_INFINITY);
        }
    }

    @Override
    protected SetRelation getWeightAttributeValueRelation() {
        return SetRelation.SUPERSET;
    }

    @Override
    public ExampleSet apply(ExampleSet exampleSet) throws OperatorException {
        if (exampleSet.getAttributes().getWeight() == null) {
            Attribute weight = AttributeFactory.createAttribute(Attributes.WEIGHT_NAME, Ontology.NUMERICAL);
            exampleSet.getExampleTable().addAttribute(weight);
            exampleSet.getAttributes().addRegular(weight);
            exampleSet.getAttributes().setWeight(weight);

            Attribute label = exampleSet.getAttributes().getLabel();
            exampleSet.recalculateAttributeStatistics(label);
            NominalMapping labelMapping = label.getMapping();
            Map<String, Double> labelFrequencies = new HashMap<String, Double>();
            for (String labelName : labelMapping.getValues()) {
                labelFrequencies.put(labelName, exampleSet.getStatistics(label, Statistics.COUNT, labelName));
            }
            double numberOfLabels = labelFrequencies.size();
            double perLabelWeight = getParameterAsDouble(PARAMETER_TOTAL_WEIGHT) / numberOfLabels;
            for (Example example : exampleSet) {
                double exampleWeight = perLabelWeight
                        / labelFrequencies.get(labelMapping.mapIndex((int) example.getValue(label)));
                example.setValue(weight, exampleWeight);
            }
        }
        return exampleSet;
    }

    @Override
    public List<ParameterType> getParameterTypes() {
        List<ParameterType> types = super.getParameterTypes();
        ParameterType type = new ParameterTypeDouble(PARAMETER_TOTAL_WEIGHT,
                "The total weight distributed over all examples.", Double.NEGATIVE_INFINITY,
                Double.POSITIVE_INFINITY, 1);
        type.setExpert(false);
        types.add(type);
        return types;
    }

    @Override
    public boolean writesIntoExistingData() {
        if (getCompatibilityLevel().isAbove(VERSION_MAY_WRITE_INTO_DATA)) {
            return true;
        } else {
            // old version: true only if original output port is connected
            return isOriginalOutputConnected();
        }
    }

    @Override
    public ResourceConsumptionEstimator getResourceConsumptionEstimator() {
        return OperatorResourceConsumptionHandler.getResourceConsumptionEstimator(getInputPort(),
                EqualLabelWeighting.class, null);
    }

    @Override
    public OperatorVersion[] getIncompatibleVersionChanges() {
        return (OperatorVersion[]) ArrayUtils.addAll(super.getIncompatibleVersionChanges(),
                new OperatorVersion[] { VERSION_MAY_WRITE_INTO_DATA });
    }
}