Examples with OutlierResult de.lmu.ifi.dbs.elki.result.outlier.OutlierResult used on opensource projects

Example 46 with OutlierResult

use of de.lmu.ifi.dbs.elki.result.outlier.OutlierResult in project elki by elki-project.

the class SOD method run.

/**
 * Performs the SOD algorithm on the given database.
 *
 * @param relation Data relation to process
 * @return Outlier result
 */
public OutlierResult run(Relation<V> relation) {
    SimilarityQuery<V> snnInstance = similarityFunction.instantiate(relation);
    FiniteProgress progress = LOG.isVerbose() ? new FiniteProgress("Assigning Subspace Outlier Degree", relation.size(), LOG) : null;
    final WritableDoubleDataStore sod_scores = DataStoreUtil.makeDoubleStorage(relation.getDBIDs(), DataStoreFactory.HINT_STATIC);
    WritableDataStore<SODModel> sod_models = null;
    if (models) {
        // Models requested
        sod_models = DataStoreUtil.makeStorage(relation.getDBIDs(), DataStoreFactory.HINT_STATIC, SODModel.class);
    }
    DoubleMinMax minmax = new DoubleMinMax();
    for (DBIDIter iter = relation.iterDBIDs(); iter.valid(); iter.advance()) {
        LOG.incrementProcessed(progress);
        DBIDs neighborhood = getNearestNeighbors(relation, snnInstance, iter);
        double[] center;
        long[] weightVector;
        double sod;
        if (neighborhood.size() > 0) {
            center = Centroid.make(relation, neighborhood).getArrayRef();
            // Note: per-dimension variances; no covariances.
            double[] variances = computePerDimensionVariances(relation, center, neighborhood);
            double expectationOfVariance = Mean.of(variances);
            weightVector = BitsUtil.zero(variances.length);
            for (int d = 0; d < variances.length; d++) {
                if (variances[d] < alpha * expectationOfVariance) {
                    BitsUtil.setI(weightVector, d);
                }
            }
            sod = subspaceOutlierDegree(relation.get(iter), center, weightVector);
        } else {
            center = relation.get(iter).toArray();
            weightVector = null;
            sod = 0.;
        }
        if (sod_models != null) {
            sod_models.put(iter, new SODModel(center, weightVector));
        }
        sod_scores.putDouble(iter, sod);
        minmax.put(sod);
    }
    LOG.ensureCompleted(progress);
    // combine results.
    OutlierScoreMeta meta = new BasicOutlierScoreMeta(minmax.getMin(), minmax.getMax());
    OutlierResult sodResult = new OutlierResult(meta, new MaterializedDoubleRelation("Subspace Outlier Degree", "sod-outlier", sod_scores, relation.getDBIDs()));
    if (sod_models != null) {
        Relation<SODModel> models = new MaterializedRelation<>("Subspace Outlier Model", "sod-outlier", new SimpleTypeInformation<>(SODModel.class), sod_models, relation.getDBIDs());
        sodResult.addChildResult(models);
    }
    return sodResult;
}

Example 47 with OutlierResult

use of de.lmu.ifi.dbs.elki.result.outlier.OutlierResult in project elki by elki-project.

the class COPTest method testCOP.

@Test
public void testCOP() {
    Database db = makeSimpleDatabase(UNITTEST + "outlier-parabolic.ascii", 530);
    OutlierResult result = // 
    new ELKIBuilder<COP<DoubleVector>>(COP.class).with(COP.Parameterizer.K_ID, 30).build().run(db);
    testAUC(db, "Noise", result, 0.89476666);
    testSingleScore(result, 416, 0.26795866);
}

Example 48 with OutlierResult

use of de.lmu.ifi.dbs.elki.result.outlier.OutlierResult in project elki by elki-project.

the class COPTest method testCOPRANSAC.

@Test
public void testCOPRANSAC() {
    Database db = makeSimpleDatabase(UNITTEST + "outlier-parabolic.ascii", 530);
    OutlierResult result = // 
    new ELKIBuilder<COP<DoubleVector>>(COP.class).with(COP.Parameterizer.K_ID, // 
    30).with(COP.Parameterizer.PCARUNNER_ID, // 
    AutotuningPCA.class).with(AutotuningPCA.Parameterizer.PCA_EIGENPAIR_FILTER, // 
    PercentageEigenPairFilter.class).with(AutotuningPCA.Parameterizer.PCA_COVARIANCE_MATRIX, // 
    RANSACCovarianceMatrixBuilder.class).with(RANSACCovarianceMatrixBuilder.Parameterizer.ITER_ID, // 
    25).with(RANSACCovarianceMatrixBuilder.Parameterizer.SEED_ID, // 
    0).build().run(db);
    testAUC(db, "Noise", result, 0.89526);
    testSingleScore(result, 416, 0.382879);
}

Example 49 with OutlierResult

use of de.lmu.ifi.dbs.elki.result.outlier.OutlierResult in project elki by elki-project.

the class ABODTest method testABOD.

@Test
public void testABOD() {
    Database db = makeSimpleDatabase(UNITTEST + "outlier-3d-3clusters.ascii", 960);
    OutlierResult result = new ELKIBuilder<ABOD<DoubleVector>>(ABOD.class).build().run(db);
    testAUC(db, "Noise", result, 0.9297962962962);
    testSingleScore(result, 945, 2.0897348547799E-5);
}

Example 50 with OutlierResult

use of de.lmu.ifi.dbs.elki.result.outlier.OutlierResult in project elki by elki-project.

the class KNNSOSTest method testToyExample.

@Test
public void testToyExample() {
    Database db = makeSimpleDatabase(UNITTEST + "outlier-3d-3clusters.ascii", 960);
    OutlierResult result = // 
    new ELKIBuilder<KNNSOS<DoubleVector>>(KNNSOS.class).with(KNNSOS.Parameterizer.KNN_ID, 150).build().run(db);
    testAUC(db, "Noise", result, 0.94435185);
    testSingleScore(result, 945, 0.05163418);
}