1 files changed, 211 insertions, 0 deletions
diff --git a/src/de/lmu/ifi/dbs/elki/evaluation/outlier/OutlierRankingEvaluation.java b/src/de/lmu/ifi/dbs/elki/evaluation/outlier/OutlierRankingEvaluation.java
new file mode 100644
index 00000000..f78a9790
--- /dev/null
+++ b/src/de/lmu/ifi/dbs/elki/evaluation/outlier/OutlierRankingEvaluation.java
@@ -0,0 +1,211 @@
+package de.lmu.ifi.dbs.elki.evaluation.outlier;
+
+/*
+ This file is part of ELKI:
+ Environment for Developing KDD-Applications Supported by Index-Structures
+
+ Copyright (C) 2014
+ 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.List;
+import java.util.regex.Pattern;
+
+import de.lmu.ifi.dbs.elki.database.Database;
+import de.lmu.ifi.dbs.elki.database.ids.DBIDUtil;
+import de.lmu.ifi.dbs.elki.database.ids.DBIDs;
+import de.lmu.ifi.dbs.elki.database.ids.SetDBIDs;
+import de.lmu.ifi.dbs.elki.evaluation.Evaluator;
+import de.lmu.ifi.dbs.elki.evaluation.scores.AveragePrecisionEvaluation;
+import de.lmu.ifi.dbs.elki.evaluation.scores.MaximumF1Evaluation;
+import de.lmu.ifi.dbs.elki.evaluation.scores.PrecisionAtKEvaluation;
+import de.lmu.ifi.dbs.elki.evaluation.scores.ROCEvaluation;
+import de.lmu.ifi.dbs.elki.evaluation.scores.adapter.DBIDsTest;
+import de.lmu.ifi.dbs.elki.evaluation.scores.adapter.OutlierScoreAdapter;
+import de.lmu.ifi.dbs.elki.evaluation.scores.adapter.SimpleAdapter;
+import de.lmu.ifi.dbs.elki.logging.Logging;
+import de.lmu.ifi.dbs.elki.logging.statistics.DoubleStatistic;
+import de.lmu.ifi.dbs.elki.result.EvaluationResult;
+import de.lmu.ifi.dbs.elki.result.EvaluationResult.MeasurementGroup;
+import de.lmu.ifi.dbs.elki.result.HierarchicalResult;
+import de.lmu.ifi.dbs.elki.result.OrderingResult;
+import de.lmu.ifi.dbs.elki.result.Result;
+import de.lmu.ifi.dbs.elki.result.ResultUtil;
+import de.lmu.ifi.dbs.elki.result.outlier.OutlierResult;
+import de.lmu.ifi.dbs.elki.utilities.DatabaseUtil;
+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;
+
+/**
+ * Evaluate outlier scores by their ranking
+ * 
+ * @author Erich Schubert
+ * 
+ * @apiviz.landmark
+ * 
+ * @apiviz.uses OutlierResult
+ * @apiviz.has EvaluationResult oneway - - «create»
+ */
+public class OutlierRankingEvaluation implements Evaluator {
+  /**
+   * The logger.
+   */
+  private static final Logging LOG = Logging.getLogger(OutlierRankingEvaluation.class);
+
+  /**
+   * The pattern to identify positive classes.
+   * 
+   * <p>
+   * Key: {@code -rocauc.positive}
+   * </p>
+   */
+  public static final OptionID POSITIVE_CLASS_NAME_ID = new OptionID("outliereval.positive", "Class label for the 'positive' class.");
+
+  /**
+   * Stores the "positive" class.
+   */
+  private Pattern positiveClassName;
+
+  /**
+   * Key prefix for statistics logging.
+   */
+  private String key = OutlierRankingEvaluation.class.getName();
+
+  /**
+   * Constructor.
+   * 
+   * @param positive_class_name Positive class name pattern
+   */
+  public OutlierRankingEvaluation(Pattern positive_class_name) {
+    super();
+    this.positiveClassName = positive_class_name;
+  }
+
+  private EvaluationResult evaluateOutlierResult(int size, SetDBIDs positiveids, OutlierResult or) {
+    EvaluationResult res = new EvaluationResult("Evaluation of ranking", "ranking-evaluation");
+    DBIDsTest test = new DBIDsTest(positiveids);
+
+    MeasurementGroup g = res.newGroup("Evaluation measures");
+    double rocauc = ROCEvaluation.STATIC.evaluate(test, new OutlierScoreAdapter(or));
+    g.addMeasure("ROC AUC", rocauc, 0., 1. ,.5, false);
+    double avep = AveragePrecisionEvaluation.STATIC.evaluate(test, new OutlierScoreAdapter(or));
+    g.addMeasure("Average Precision", avep, 0., 1., 0., false);
+    double rprec = PrecisionAtKEvaluation.RPRECISION.evaluate(test, new OutlierScoreAdapter(or));
+    g.addMeasure("R-Precision", rprec, 0., 1., 0., false);
+    double maxf1 = MaximumF1Evaluation.STATIC.evaluate(test, new OutlierScoreAdapter(or));
+    g.addMeasure("Maximum F1", maxf1, 0., 1., 0., false);
+    if(LOG.isStatistics()) {
+      LOG.statistics(new DoubleStatistic(key + ".rocauc", rocauc));
+      LOG.statistics(new DoubleStatistic(key + ".precision.average", rocauc));
+      LOG.statistics(new DoubleStatistic(key + ".precision.r", rocauc));
+      LOG.statistics(new DoubleStatistic(key + ".f1.maximum", rocauc));
+    }
+    return res;
+  }
+
+  private EvaluationResult evaluateOrderingResult(int size, SetDBIDs positiveids, DBIDs order) {
+    if(order.size() != size) {
+      throw new IllegalStateException("Iterable result doesn't match database size - incomplete ordering?");
+    }
+
+    EvaluationResult res = new EvaluationResult("Evaluation of ranking", "ranking-evaluation");
+    DBIDsTest test = new DBIDsTest(positiveids);
+
+    MeasurementGroup g = res.newGroup("Evaluation measures");
+    double rocauc = ROCEvaluation.STATIC.evaluate(test, new SimpleAdapter(order.iter()));
+    g.addMeasure("ROC AUC", rocauc, 0., 1. ,.5, false);
+    double avep = AveragePrecisionEvaluation.STATIC.evaluate(test, new SimpleAdapter(order.iter()));
+    g.addMeasure("Average Precision", avep, 0., 1., 0., false);
+    double rprec = PrecisionAtKEvaluation.RPRECISION.evaluate(test, new SimpleAdapter(order.iter()));
+    g.addMeasure("R-Precision", rprec, 0., 1., 0., false);
+    double maxf1 = MaximumF1Evaluation.STATIC.evaluate(test, new SimpleAdapter(order.iter()));
+    g.addMeasure("Maximum F1", maxf1, 0., 1., 0., false);
+    if(LOG.isStatistics()) {
+      LOG.statistics(new DoubleStatistic(key + ".rocauc", rocauc));
+      LOG.statistics(new DoubleStatistic(key + ".precision.average", rocauc));
+      LOG.statistics(new DoubleStatistic(key + ".precision.r", rocauc));
+      LOG.statistics(new DoubleStatistic(key + ".f1.maximum", rocauc));
+    }
+    return res;
+  }
+
+  @Override
+  public void processNewResult(HierarchicalResult baseResult, Result result) {
+    Database db = ResultUtil.findDatabase(baseResult);
+    SetDBIDs positiveids = DBIDUtil.ensureSet(DatabaseUtil.getObjectsByLabelMatch(db, positiveClassName));
+
+    if(positiveids.size() == 0) {
+      LOG.warning("Cannot evaluate outlier results - no objects matched the given pattern.");
+      return;
+    }
+
+    boolean nonefound = true;
+    List<OutlierResult> oresults = ResultUtil.getOutlierResults(result);
+    List<OrderingResult> orderings = ResultUtil.getOrderingResults(result);
+    // Outlier results are the main use case.
+    for(OutlierResult o : oresults) {
+      db.getHierarchy().add(o, evaluateOutlierResult(o.getScores().size(), positiveids, o));
+      // Process them only once.
+      orderings.remove(o.getOrdering());
+      nonefound = false;
+    }
+
+    // FIXME: find appropriate place to add the derived result
+    // otherwise apply an ordering to the database IDs.
+    for(OrderingResult or : orderings) {
+      DBIDs sorted = or.iter(or.getDBIDs());
+      db.getHierarchy().add(or, evaluateOrderingResult(or.getDBIDs().size(), positiveids, sorted));
+      nonefound = false;
+    }
+
+    if(nonefound) {
+      return;
+      // logger.warning("No results found to process with ROC curve analyzer. Got "+iterables.size()+" iterables, "+orderings.size()+" orderings.");
+    }
+  }
+
+  /**
+   * Parameterization class.
+   * 
+   * @author Erich Schubert
+   * 
+   * @apiviz.exclude
+   */
+  public static class Parameterizer extends AbstractParameterizer {
+    /**
+     * Pattern for positive class.
+     */
+    protected Pattern positiveClassName = null;
+
+    @Override
+    protected void makeOptions(Parameterization config) {
+      super.makeOptions(config);
+      PatternParameter positiveClassNameP = new PatternParameter(POSITIVE_CLASS_NAME_ID);
+      if(config.grab(positiveClassNameP)) {
+        positiveClassName = positiveClassNameP.getValue();
+      }
+    }
+
+    @Override
+    protected OutlierRankingEvaluation makeInstance() {
+      return new OutlierRankingEvaluation(positiveClassName);
+    }
+  }
+}