A B C D E F G H I J K L M N O P Q R S T U V W X Y
All Classes All Packages

U

unboxVectors(List<? extends NumberVector>) - Static method in class elki.clustering.kmeans.initialization.AbstractKMeansInitialization

Unbox database means to primitive means.

unclaimedids - Variable in class elki.clustering.optics.OPTICSXi.ClusterHierarchyBuilder

Unclaimed objects that will be assigned to a top level or noise cluster in the end.

UNCLUSTERED - Static variable in class elki.evaluation.clustering.pairsegments.Segment

Object is not clustered

UNDEFINED_DISTANCE - Static variable in class elki.clustering.optics.FastOPTICS

undefined value for (reachability/average) distance

unifySegment(Segment) - Method in class elki.evaluation.clustering.pairsegments.Segments

union(Relation<? extends NumberVector>, ORCLUS.ORCLUSCluster, ORCLUS.ORCLUSCluster, int) - Method in class elki.clustering.correlation.ORCLUS

Returns the union of the two specified clusters.

unionDBIDs(DBIDs[], int, int) - Method in class elki.clustering.subspace.P3C

Compute the union of multiple DBID sets.

UNPROCESSED - Static variable in class elki.clustering.dbscan.GeneralizedDBSCAN.Instance

Unprocessed IDs

UNPROCESSED - Static variable in class elki.clustering.dbscan.GriDBSCAN.Instance

Unprocessed IDs.

UNPROCESSED - Static variable in class elki.clustering.dbscan.LSDBC

Constants used internally.

update(Border) - Method in class elki.clustering.dbscan.util.MultiBorder

Add a new border to the existing borders.

updateAssignment(double[][], double[][], int[]) - Method in class elki.clustering.affinitypropagation.AffinityPropagation

Update the cluster assignment.

updateAssignment(ArrayModifiableDBIDs, DBIDArrayIter, DBIDRef, int) - Method in class elki.clustering.kmedoids.FastPAM1.Instance

Update an existing cluster assignment.

updateAvailabilities(double[][], double[][]) - Method in class elki.clustering.affinitypropagation.AffinityPropagation

Update availability matrix

updateBounds(double[]) - Method in class elki.clustering.kmeans.HamerlyKMeans.Instance

Update the bounds for k-means.

updateBounds(double[]) - Method in class elki.clustering.kmeans.SimplifiedElkanKMeans.Instance

Update the bounds for k-means.

updateBounds(double[]) - Method in class elki.clustering.kmeans.spherical.EuclideanSphericalHamerlyKMeans.Instance

Update the bounds for k-means.

updateBounds(double[]) - Method in class elki.clustering.kmeans.spherical.EuclideanSphericalSimplifiedElkanKMeans.Instance

Update the bounds for k-means.

updateBounds(double[]) - Method in class elki.clustering.kmeans.spherical.SphericalHamerlyKMeans.Instance

Update the bounds for k-means.

updateBounds(double[]) - Method in class elki.clustering.kmeans.spherical.SphericalSimplifiedElkanKMeans.Instance

Update the bounds for k-means.

updateBounds(double[]) - Method in class elki.clustering.kmeans.spherical.SphericalSimplifiedHamerlyKMeans.Instance

Update the bounds for k-means.

updateCache(double[], double[], int[], int, int, int, double) - Static method in class elki.clustering.hierarchical.Anderberg.Instance

Update the cache.

updateCenters() - Method in class elki.clustering.kmeans.YinYangKMeans.Instance

Update centers and how much they moved.

updateCholesky(double[][], CholeskyDecomposition) - Static method in class elki.clustering.em.models.MultivariateGaussianModel

Update the cholesky decomposition.

updateCoreBorderObjects(int) - Method in class elki.clustering.dbscan.GriDBSCAN.Instance

Update the shared arrays for core points (to conserve memory)

updateE(double[], double[][], double, double) - Method in class elki.clustering.em.models.TextbookMultivariateGaussianModel

Add a set of points with covariance information, for KDTreeEM.

updateE(NumberVector, double) - Method in class elki.clustering.em.models.DiagonalGaussianModel

updateE(NumberVector, double) - Method in class elki.clustering.em.models.MultivariateGaussianModel

updateE(NumberVector, double) - Method in class elki.clustering.em.models.SphericalGaussianModel

updateE(NumberVector, double) - Method in class elki.clustering.em.models.TextbookMultivariateGaussianModel

updateE(NumberVector, double) - Method in class elki.clustering.em.models.TextbookSphericalGaussianModel

updateE(NumberVector, double) - Method in class elki.clustering.em.models.TwoPassMultivariateGaussianModel

Second pass: compute the covariance matrix.

updateE(ClusterFeature, double) - Method in interface elki.clustering.em.models.BetulaClusterModel

Process one clustering feature in the E step.

updateE(ClusterFeature, double) - Method in class elki.clustering.em.models.DiagonalGaussianModel

updateE(ClusterFeature, double) - Method in class elki.clustering.em.models.MultivariateGaussianModel

updateE(ClusterFeature, double) - Method in class elki.clustering.em.models.SphericalGaussianModel

updateE(O, double) - Method in interface elki.clustering.em.models.EMClusterModel

Process one data point in the E step

updateEntry(int, int) - Method in class elki.clustering.hierarchical.HACAM.Instance

Update entry at x,y for distance matrix distances

updateEntry(int, int) - Method in class elki.clustering.hierarchical.MiniMax.Instance

Update entry at x,y for distance matrix distances

updateFilterSDASet(double, List<OPTICSXi.SteepDownArea>, double) - Static method in class elki.clustering.optics.OPTICSXi

Update the mib values of SteepDownAreas, and remove obsolete areas.

updateGroupAssignment(int, double[][], int[]) - Method in class elki.clustering.kmeans.YinYangKMeans.Instance

Perform one step of Voronoi refinement.

updateMatrices(int) - Method in class elki.clustering.hierarchical.MiniMax.Instance

Update the entries of the matrices that contain a distance to c, the newly merged cluster.

updateMatrices(int, int) - Method in class elki.clustering.hierarchical.HACAM.Instance

Update the entries of the matrices that contain a distance to y, the newly merged cluster.

updateMatrices(int, int) - Method in class elki.clustering.hierarchical.MiniMaxAnderberg.Instance

Update the entries of the matrices that contain a distance to y, the newly merged cluster.

updateMatrix(double, int, int, int, int) - Method in class elki.clustering.hierarchical.AGNES.Instance

Update the scratch distance matrix.

updateMatrix(double, int, int, int, int) - Method in class elki.clustering.hierarchical.Anderberg.Instance

updateMatrix(int, int) - Method in class elki.clustering.hierarchical.MedoidLinkage.Instance

Update the scratch distance matrix.

updateMeanAndAssignment(int, NumberVector, DBIDIter) - Method in class elki.clustering.kmeans.MacQueenKMeans.Instance

Try to update the cluster assignment.

updateMeans(Relation<V>, WritableDataStore<double[]>, double[][], int) - Method in class elki.clustering.kmeans.FuzzyCMeans

Updates the means according to the weighted means of all data points.

updateMinMax(NumberVector, double[], double[]) - Method in class elki.clustering.subspace.CLIQUE

Updates the minima and maxima array according to the specified feature vector.

updatePriorCost(double[]) - Method in class elki.clustering.kmedoids.FastPAM1.Instance

Prior assignment costs.

updateRemovalLoss(double[]) - Method in class elki.clustering.silhouette.FastMSC.Instance

Update the share removal loss data

updateResponsibilities(double[][], double[][], double[][]) - Method in class elki.clustering.affinitypropagation.AffinityPropagation

Update the responsibility matrix

updateRowAndColumnMeans(double[][], boolean) - Method in class elki.clustering.biclustering.ChengAndChurch.BiclusterCandidate

Update the row means and column means.

updateSecondNearest(DBIDRef, DBIDArrayIter, int, double, int) - Method in class elki.clustering.kmedoids.FastPAM1.Instance

Find the second nearest medoid.

updateThirdNearest(DBIDRef, FastMSC.Record, int, double, DBIDArrayIter) - Method in class elki.clustering.silhouette.FastMSC.Instance

Update the third nearest in the record.

updateWeights(double[], double[][]) - Method in class elki.clustering.hierarchical.birch.BIRCHKMeansPlusPlus

Update the weight list.

updateWeights(NumberVector) - Method in class elki.clustering.kmeans.initialization.SphericalKMeansPlusPlus.Instance

Update the weight list.

updateWeights(ClusterFeature, List<? extends AsClusterFeature>, double[]) - Method in class elki.clustering.kmeans.initialization.betula.CFKPlusPlusLeaves

Update the weight list.

updateWeights(T) - Method in class elki.clustering.kmeans.initialization.KMeansPlusPlus.Instance

Update the weight list.

upper - Variable in class elki.clustering.kmeans.HamerlyKMeans.Instance

Upper bounds

upper - Variable in class elki.clustering.kmeans.SimplifiedElkanKMeans.Instance

Upper bounds

upper - Variable in class elki.clustering.kmeans.spherical.EuclideanSphericalHamerlyKMeans.Instance

Upper bounds

upper - Variable in class elki.clustering.kmeans.spherical.EuclideanSphericalSimplifiedElkanKMeans.Instance

Upper bounds

upper - Variable in class elki.clustering.kmeans.YinYangKMeans.Instance

Upper bound

upperBoundMI() - Method in class elki.evaluation.clustering.Entropy

Get an upper bound for the mutual information (for scaling).

upperBoundVI() - Method in class elki.evaluation.clustering.Entropy

Get an upper bound for the VI (for scaling).

useinverted - Variable in class elki.clustering.biclustering.ChengAndChurch

Allow inversion of rows in the last phase.

usim - Variable in class elki.clustering.kmeans.spherical.SphericalHamerlyKMeans.Instance

Similarity upper bound.

usim - Variable in class elki.clustering.kmeans.spherical.SphericalSimplifiedElkanKMeans.Instance

Similarity upper bound.

usim - Variable in class elki.clustering.kmeans.spherical.SphericalSimplifiedHamerlyKMeans.Instance

Similarity upper bound.

A B C D E F G H I J K L M N O P Q R S T U V W X Y
All Classes All Packages