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package de.lmu.ifi.dbs.elki.algorithm.outlier.trivial;
/*
This file is part of ELKI:
Environment for Developing KDD-Applications Supported by Index-Structures
Copyright (C) 2012
Ludwig-Maximilians-Universität München
Lehr- und Forschungseinheit für Datenbanksysteme
ELKI Development Team
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/>.
*/
import java.util.regex.Pattern;
import de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm;
import de.lmu.ifi.dbs.elki.algorithm.outlier.OutlierAlgorithm;
import de.lmu.ifi.dbs.elki.data.ClassLabel;
import de.lmu.ifi.dbs.elki.data.type.NoSupportedDataTypeException;
import de.lmu.ifi.dbs.elki.data.type.TypeInformation;
import de.lmu.ifi.dbs.elki.data.type.TypeUtil;
import de.lmu.ifi.dbs.elki.database.Database;
import de.lmu.ifi.dbs.elki.database.datastore.DataStoreFactory;
import de.lmu.ifi.dbs.elki.database.datastore.DataStoreUtil;
import de.lmu.ifi.dbs.elki.database.datastore.WritableDoubleDataStore;
import de.lmu.ifi.dbs.elki.database.ids.DBID;
import de.lmu.ifi.dbs.elki.database.relation.MaterializedRelation;
import de.lmu.ifi.dbs.elki.database.relation.Relation;
import de.lmu.ifi.dbs.elki.logging.Logging;
import de.lmu.ifi.dbs.elki.result.outlier.OutlierResult;
import de.lmu.ifi.dbs.elki.result.outlier.OutlierScoreMeta;
import de.lmu.ifi.dbs.elki.result.outlier.ProbabilisticOutlierScore;
import de.lmu.ifi.dbs.elki.utilities.optionhandling.AbstractParameterizer;
import de.lmu.ifi.dbs.elki.utilities.optionhandling.OptionID;
import de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.Parameterization;
import de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.PatternParameter;
/**
* Trivial algorithm that marks outliers by their label. Can be used as
* reference algorithm in comparisons.
*
* @author Erich Schubert
*/
public class ByLabelOutlier extends AbstractAlgorithm<OutlierResult> implements OutlierAlgorithm {
/**
* Our logger.
*/
private static final Logging logger = Logging.getLogger(ByLabelOutlier.class);
/**
* The default pattern to use.
*/
public static final String DEFAULT_PATTERN = ".*(Outlier|Noise).*";
/**
* The pattern we match with.
*/
final Pattern pattern;
/**
* Constructor.
*
* @param pattern Pattern to match with.
*/
public ByLabelOutlier(Pattern pattern) {
super();
this.pattern = pattern;
}
/**
* Constructor.
*/
public ByLabelOutlier() {
this(Pattern.compile(DEFAULT_PATTERN));
}
@Override
public TypeInformation[] getInputTypeRestriction() {
return TypeUtil.array(TypeUtil.GUESSED_LABEL);
}
@Override
public OutlierResult run(Database database) {
// Prefer a true class label
try {
Relation<ClassLabel> relation = database.getRelation(TypeUtil.CLASSLABEL);
return run(relation);
}
catch(NoSupportedDataTypeException e) {
// Otherwise, try any labellike.
return run(database.getRelation(getInputTypeRestriction()[0]));
}
}
/**
* Run the algorithm
*
* @param relation Relation to process.
* @return Result
*/
public OutlierResult run(Relation<?> relation) {
WritableDoubleDataStore scores = DataStoreUtil.makeDoubleStorage(relation.getDBIDs(), DataStoreFactory.HINT_HOT);
for(DBID id : relation.iterDBIDs()) {
String label = relation.get(id).toString();
final double score;
if (pattern.matcher(label).matches()) {
score = 1.0;
} else {
score = 0.0;
}
scores.putDouble(id, score);
}
Relation<Double> scoreres = new MaterializedRelation<Double>("By label outlier scores", "label-outlier", TypeUtil.DOUBLE, scores, relation.getDBIDs());
OutlierScoreMeta meta = new ProbabilisticOutlierScore();
return new OutlierResult(meta, scoreres);
}
@Override
protected Logging getLogger() {
return logger;
}
/**
* Parameterization class.
*
* @author Erich Schubert
*
* @apiviz.exclude
*/
public static class Parameterizer extends AbstractParameterizer {
/**
* The pattern to match outliers with.
*
* <p>
* Default value: .*(Outlier|Noise).*
* </p>
* <p>
* Key: {@code -outlier.pattern}
* </p>
*/
public static final OptionID OUTLIER_PATTERN_ID = OptionID.getOrCreateOptionID("outlier.pattern", "Label pattern to match outliers.");
/**
* Stores the "outlier" class.
*/
private Pattern pattern;
@Override
protected void makeOptions(Parameterization config) {
super.makeOptions(config);
PatternParameter patternP = new PatternParameter(OUTLIER_PATTERN_ID, DEFAULT_PATTERN);
if(config.grab(patternP)) {
pattern = patternP.getValue();
}
}
@Override
protected ByLabelOutlier makeInstance() {
return new ByLabelOutlier(pattern);
}
}
}
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