Examples of OutlierScoreMeta

de.lmu.ifi.dbs.elki.result.outlier.OutlierScoreMeta
Generic meta information about the value range of an outlier score. All values can be {@link Double#NaN} if not specified by the algorithm or notcomputed (actual values). For theoretical values, it is explicitly allowed to return {@link Double#NEGATIVE_INFINITY} or {@link Double#POSITIVE_INFINITY}. @author Erich Schubert

Examples of de.lmu.ifi.dbs.elki.result.outlier.OutlierScoreMeta

      }
      if(cprog != null) {
        cprog.ensureCompleted(logger);
      }
    }
    OutlierScoreMeta meta = new BasicOutlierScoreMeta(minmax.getMin(), minmax.getMax());
    Relation<Double> scoreres = new MaterializedRelation<Double>("Feature bagging", "fb-outlier", TypeUtil.DOUBLE, scores, relation.getDBIDs());
    return new OutlierResult(meta, scoreres);
  }

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Examples of de.lmu.ifi.dbs.elki.result.outlier.OutlierScoreMeta

    if(progress != null) {
      progress.ensureCompleted(logger);
    }
    // combine results.
    Relation<SODModel<?>> models = new MaterializedRelation<SODModel<?>>("Subspace Outlier Model", "sod-outlier", new SimpleTypeInformation<SODModel<?>>(SODModel.class), sod_models, relation.getDBIDs());
    OutlierScoreMeta meta = new BasicOutlierScoreMeta(minmax.getMin(), minmax.getMax());
    OutlierResult sodResult = new OutlierResult(meta, new SODProxyScoreResult(models, relation.getDBIDs()));
    // also add the models.
    sodResult.addChildResult(models);
    return sodResult;
  }

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Examples of de.lmu.ifi.dbs.elki.result.outlier.OutlierScoreMeta

      }
    }


    // Build result representation.
    Relation<Double> scoreResult = new MaterializedRelation<Double>("Influence Outlier Score", "inflo-outlier", TypeUtil.DOUBLE, inflos, relation.getDBIDs());
    OutlierScoreMeta scoreMeta = new QuotientOutlierScoreMeta(inflominmax.getMin(), inflominmax.getMax(), 0.0, Double.POSITIVE_INFINITY, 1.0);
    return new OutlierResult(scoreMeta, scoreResult);
  }

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Examples of de.lmu.ifi.dbs.elki.result.outlier.OutlierScoreMeta

    if(progressKNNWeight != null) {
      progressKNNWeight.ensureCompleted(logger);
    }


    Relation<Double> res = new MaterializedRelation<Double>("Weighted kNN Outlier Score", "knnw-outlier", TypeUtil.DOUBLE, knnw_score, relation.getDBIDs());
    OutlierScoreMeta meta = new BasicOutlierScoreMeta(minmax.getMin(), minmax.getMax(), 0.0, Double.POSITIVE_INFINITY, 0.0);
    return new OutlierResult(meta, res);
  }

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Examples of de.lmu.ifi.dbs.elki.result.outlier.OutlierScoreMeta

    WritableDataStore<Double> scores = DataStoreUtil.makeStorage(relation.getDBIDs(), DataStoreFactory.HINT_HOT, Double.class);
    for(DBID id : relation.iterDBIDs()) {
      scores.put(id, 0.0);
    }
    Relation<Double> scoreres = new MaterializedRelation<Double>("Trivial no-outlier score", "no-outlier", TypeUtil.DOUBLE, scores, relation.getDBIDs());
    OutlierScoreMeta meta = new ProbabilisticOutlierScore();
    return new OutlierResult(meta, scoreres);
  }

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Examples of de.lmu.ifi.dbs.elki.result.outlier.OutlierScoreMeta

      // update minimum and maximum
      ofminmax.put(of);
    }
    // Build result representation.
    Relation<Double> scoreResult = new MaterializedRelation<Double>("OPTICS Outlier Scores", "optics-outlier", TypeUtil.DOUBLE, ofs, relation.getDBIDs());
    OutlierScoreMeta scoreMeta = new QuotientOutlierScoreMeta(ofminmax.getMin(), ofminmax.getMax(), 0.0, Double.POSITIVE_INFINITY, 1.0);
    return new OutlierResult(scoreMeta, scoreResult);
  }

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Examples of de.lmu.ifi.dbs.elki.result.outlier.OutlierScoreMeta

    // Run the actual score process
    DataStore<Double> dbodscore = computeOutlierScores(database, distFunc, d);


    // Build result representation.
    Relation<Double> scoreResult = new MaterializedRelation<Double>("Density-Based Outlier Detection", "db-outlier", TypeUtil.DOUBLE, dbodscore, relation.getDBIDs());
    OutlierScoreMeta scoreMeta = new ProbabilisticOutlierScore();
    return new OutlierResult(scoreMeta, scoreResult);
  }

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Examples of de.lmu.ifi.dbs.elki.result.outlier.OutlierScoreMeta

        score = 0.0;
      }
      scores.put(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);
  }

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Examples of de.lmu.ifi.dbs.elki.result.outlier.OutlierScoreMeta

    WritableDataStore<Double> scores = DataStoreUtil.makeStorage(relation.getDBIDs(), DataStoreFactory.HINT_HOT, Double.class);
    for(DBID id : relation.iterDBIDs()) {
      scores.put(id, 1.0);
    }
    Relation<Double> scoreres = new MaterializedRelation<Double>("Trivial all-outlier score", "all-outlier", TypeUtil.DOUBLE, scores, relation.getDBIDs());
    OutlierScoreMeta meta = new ProbabilisticOutlierScore();
    return new OutlierResult(meta, scoreres);
  }

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Examples of de.lmu.ifi.dbs.elki.result.outlier.OutlierScoreMeta

      }
      emo_score.put(id, maxProb);
      globmax = Math.max(maxProb, globmax);
    }
    Relation<Double> scoreres = new MaterializedRelation<Double>("EM outlier scores", "em-outlier", TypeUtil.DOUBLE, emo_score, relation.getDBIDs());
    OutlierScoreMeta meta = new ProbabilisticOutlierScore(0.0, globmax);
    // combine results.
    OutlierResult result = new OutlierResult(meta, scoreres);
    // TODO: add a keep-EM flag?
    result.addChildResult(emresult);
    return result;

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