Examples with NumericalFeatureSelection de.lmu.ifi.dbs.elki.data.projection.NumericalFeatureSelection used on opensource projects

Example 1 with NumericalFeatureSelection

use of de.lmu.ifi.dbs.elki.data.projection.NumericalFeatureSelection in project elki by elki-project.

the class HiCS method run.

/**
 * Perform HiCS on a given database.
 *
 * @param relation the database
 * @return The aggregated resulting scores that were assigned by the given
 *         outlier detection algorithm
 */
public OutlierResult run(Relation<V> relation) {
    final DBIDs ids = relation.getDBIDs();
    ArrayList<ArrayDBIDs> subspaceIndex = buildOneDimIndexes(relation);
    Set<HiCSSubspace> subspaces = calculateSubspaces(relation, subspaceIndex, rnd.getSingleThreadedRandom());
    if (LOG.isVerbose()) {
        LOG.verbose("Number of high-contrast subspaces: " + subspaces.size());
    }
    List<DoubleRelation> results = new ArrayList<>();
    FiniteProgress prog = LOG.isVerbose() ? new FiniteProgress("Calculating Outlier scores for high Contrast subspaces", subspaces.size(), LOG) : null;
    // relation instead of SubspaceEuclideanDistanceFunction?)
    for (HiCSSubspace dimset : subspaces) {
        if (LOG.isVerbose()) {
            LOG.verbose("Performing outlier detection in subspace " + dimset);
        }
        ProxyDatabase pdb = new ProxyDatabase(ids);
        pdb.addRelation(new ProjectedView<>(relation, new NumericalFeatureSelection<V>(dimset)));
        // run LOF and collect the result
        OutlierResult result = outlierAlgorithm.run(pdb);
        results.add(result.getScores());
        LOG.incrementProcessed(prog);
    }
    LOG.ensureCompleted(prog);
    WritableDoubleDataStore scores = DataStoreUtil.makeDoubleStorage(relation.getDBIDs(), DataStoreFactory.HINT_STATIC);
    DoubleMinMax minmax = new DoubleMinMax();
    for (DBIDIter iditer = relation.iterDBIDs(); iditer.valid(); iditer.advance()) {
        double sum = 0.0;
        for (DoubleRelation r : results) {
            final double s = r.doubleValue(iditer);
            if (!Double.isNaN(s)) {
                sum += s;
            }
        }
        scores.putDouble(iditer, sum);
        minmax.put(sum);
    }
    OutlierScoreMeta meta = new BasicOutlierScoreMeta(minmax.getMin(), minmax.getMax());
    DoubleRelation scoreres = new MaterializedDoubleRelation("HiCS", "HiCS-outlier", scores, relation.getDBIDs());
    return new OutlierResult(meta, scoreres);
}