Package de.lmu.ifi.dbs.elki.distance.distancefunction.subspace

Examples of de.lmu.ifi.dbs.elki.distance.distancefunction.subspace.DimensionsSelectingEuclideanDistanceFunction$Parameterizer


    ArrayList<OutlierResult> results = new ArrayList<OutlierResult>(num);
    {
      FiniteProgress prog = logger.isVerbose() ? new FiniteProgress("LOF iterations", num, logger) : null;
      for(int i = 0; i < num; i++) {
        BitSet dimset = randomSubspace(dbdim, mindim, maxdim);
        DimensionsSelectingEuclideanDistanceFunction df = new DimensionsSelectingEuclideanDistanceFunction(dimset);
        LOF<NumberVector<?, ?>, DoubleDistance> lof = new LOF<NumberVector<?, ?>, DoubleDistance>(k, df, df);

        // run LOF and collect the result
        OutlierResult result = lof.run(relation);
        results.add(result);
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     * @param center
     * @param weightVector
     * @return sod value
     */
    private double subspaceOutlierDegree(O queryObject, O center, BitSet weightVector) {
      final DimensionsSelectingEuclideanDistanceFunction df = new DimensionsSelectingEuclideanDistanceFunction(weightVector);
      double distance = df.distance(queryObject, center).doubleValue();
      distance /= weightVector.cardinality();
      return distance;
    }
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