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N

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

Number of biclusters to be found.

n - Variable in class elki.clustering.hierarchical.birch.ClusteringFeature

Number of objects

n - Variable in class elki.index.tree.betula.features.BIRCHCF

Number of objects

n - Variable in class elki.index.tree.betula.features.VIIFeature

Number of objects

n - Variable in class elki.index.tree.betula.features.VVIFeature

Number of objects

n - Variable in class elki.index.tree.betula.features.VVVFeature

Number of objects

NaiveMeanShiftClustering<V extends elki.data.NumberVector> - Class in elki.clustering

Mean-shift based clustering algorithm.

NaiveMeanShiftClustering(NumberVectorDistance<? super V>, KernelDensityFunction, double) - Constructor for class elki.clustering.NaiveMeanShiftClustering

Constructor.

name - Variable in class elki.data.Cluster

Cluster name.

ncounter - Variable in class elki.clustering.dbscan.DBSCAN.Instance

Number of neighbors.

ncp - Variable in class elki.clustering.kmeans.HartiganWongKMeans.Instance

In Optimal-transfer-stage, NCP(L) indicates the step at which cluster L is last updated.

nearest - Variable in class elki.clustering.kmedoids.CLARANS.Assignment

Distance to the nearest medoid of each point.

nearest - Variable in class elki.clustering.kmedoids.PAM.Instance

Distance to the nearest medoid of each point.

nearestMeans(double[][], int[][]) - Static method in class elki.clustering.kmeans.AbstractKMeans

Recompute the separation of cluster means.

needsMetric() - Method in class elki.clustering.kmeans.AbstractKMeans.Par

Users could use other non-metric distances at their own risk; but some k-means variants make explicit use of the triangle inequality, we emit extra warnings then.

needsMetric() - Method in class elki.clustering.kmeans.CompareMeans.Par

needsMetric() - Method in class elki.clustering.kmeans.HamerlyKMeans.Par

needsMetric() - Method in class elki.clustering.kmeans.SimplifiedElkanKMeans.Par

needsMetric() - Method in class elki.clustering.kmeans.SortMeans.Par

needsMetric() - Method in class elki.clustering.kmeans.YinYangKMeans.Par

needsTwoPass() - Method in interface elki.clustering.em.models.EMClusterModel

True, if the model needs two passes in the E step.

needsTwoPass() - Method in class elki.clustering.em.models.TwoPassMultivariateGaussianModel

NEIGHBORHOODPRED_ID - Static variable in class elki.clustering.dbscan.GeneralizedDBSCAN.Par

Parameter for neighborhood predicate.

NEIGHBORHOODPRED_ID - Static variable in class elki.clustering.dbscan.parallel.ParallelGeneralizedDBSCAN.Par

Parameter for neighborhood predicate.

NeighborPredicate<T> - Interface in elki.clustering.dbscan.predicates

Get the neighbors of an object

NeighborPredicate.Instance<T> - Interface in elki.clustering.dbscan.predicates

Instance for a particular data set.

neighbors - Variable in class elki.clustering.dbscan.DBSCAN.Instance

Neighbor query output.

NEIGHBORS_ID - Static variable in class elki.clustering.kmedoids.CLARANS.Par

The number of neighbors to explore.

neighs - Variable in class elki.clustering.optics.FastOPTICS

neighbors of a point

newids - Variable in class elki.clustering.hierarchical.extraction.SimplifiedHierarchyExtraction.TempCluster

New ids, not yet in child clusters.

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

Scratch space for new means.

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

Scratch space for new means.

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

Scratch space for new means.

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

Scratch space for new means.

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

Scratch space for new means.

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

Scratch space for new means.

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

Scratch space for new means.

newmodels - Variable in class elki.clustering.em.KDTreeEM

Models for next iteration.

newTree(DBIDs, Relation<? extends NumberVector>) - Method in class elki.clustering.hierarchical.birch.CFTree.Factory

Make a new tree.

newTree(DBIDs, Relation<? extends NumberVector>, boolean) - Method in class elki.index.tree.betula.CFTree.Factory

Make a new tree.

next - Variable in class elki.clustering.optics.OPTICSXi.SteepScanPosition

Variable for accessing.

next() - Method in class elki.clustering.optics.OPTICSXi.SteepScanPosition

Advance to the next entry

nextclus - Variable in class elki.clustering.dbscan.parallel.ParallelGeneralizedDBSCAN.Instance

Next cluster number assigned.

nextDouble(double) - Method in class elki.clustering.kmeans.initialization.KMeansPlusPlus.Instance

nextDouble(double) - Method in class elki.clustering.kmeans.initialization.SphericalKMeansPlusPlus.Instance

nextevent - Variable in class elki.datasource.parser.ClusteringVectorParser

Event to report next.

nextEvent() - Method in class elki.datasource.parser.ClusteringVectorParser

nextIteration(double[][]) - Method in class elki.clustering.kmeans.parallel.KMeansProcessor

Initialize for a new iteration.

nmea - Variable in class elki.clustering.em.models.DiagonalGaussianModel

Temporary storage, to avoid reallocations.

nmea - Variable in class elki.clustering.em.models.MultivariateGaussianModel

Temporary storage, to avoid reallocations.

nmea - Variable in class elki.clustering.em.models.SphericalGaussianModel

Temporary storage, to avoid reallocations.

nmea - Variable in class elki.clustering.em.models.TextbookSphericalGaussianModel

Temporary storage, to avoid reallocations.

NNChain<O> - Class in elki.clustering.hierarchical

NNchain clustering algorithm.

NNChain(Distance<? super O>, Linkage) - Constructor for class elki.clustering.hierarchical.NNChain

Constructor.

NNChain.Instance - Class in elki.clustering.hierarchical

Main worker instance of NNChain.

nnChainCore() - Method in class elki.clustering.hierarchical.MiniMaxNNChain.Instance

Uses NNChain as in "Modern hierarchical, agglomerative clustering algorithms" by Daniel Müllner.

nnChainCore() - Method in class elki.clustering.hierarchical.NNChain.Instance

Uses NNChain as in "Modern hierarchical, agglomerative clustering algorithms" by Daniel Müllner.

nnChainCore(DBIDArrayIter, DBIDArrayIter, ClusterMergeHistoryBuilder, Relation<O>) - Method in class elki.clustering.hierarchical.LinearMemoryNNChain.Instance

Core function of NNChain.

NO_PENALIZE_ID - Static variable in class elki.evaluation.clustering.internal.Silhouette.Par

Do not penalize ignored noise.

NO_PENALIZE_ID - Static variable in class elki.evaluation.clustering.internal.VarianceRatioCriterion.Par

Do not penalize ignored noise.

nocorrect - Variable in class elki.clustering.optics.OPTICSXi

Disable the predecessor correction.

nocorrect - Variable in class elki.clustering.optics.OPTICSXi.Par

NOCORRECT_ID - Static variable in class elki.clustering.optics.OPTICSXi.Par

Parameter to disable the correction function.

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

Algorithm 3 of Cheng and Church.

noise - Variable in class elki.clustering.dbscan.DBSCAN.Instance

Holds a set of noise.

noise - Variable in class elki.clustering.SNNClustering

Holds a set of noise.

noise - Variable in class elki.data.Cluster

Noise?

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

Noise IDs

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

Noise IDs.

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

Constants used internally.

NOISE_FLAG_ID - Static variable in class elki.clustering.kmeans.KMeansMinusMinus.Par

Flag to produce a "noise" cluster, instead of assigning them to the nearest neighbor.

NOISE_ID - Static variable in class elki.clustering.trivial.ByLabelClustering.Par

Parameter to specify the pattern to recognize noise clusters by.

NOISE_ID - Static variable in class elki.evaluation.clustering.EvaluateClustering.Par

Parameter flag for special noise handling.

NOISE_ID - Static variable in class elki.evaluation.clustering.internal.CIndex.Par

Parameter for the option, how noise should be treated.

NOISE_ID - Static variable in class elki.evaluation.clustering.internal.ClusterRadius.Par

Parameter to treat noise as a single cluster.

NOISE_ID - Static variable in class elki.evaluation.clustering.internal.ConcordantPairsGammaTau.Par

Parameter for the option, how noise should be treated.

NOISE_ID - Static variable in class elki.evaluation.clustering.internal.DaviesBouldinIndex.Par

Parameter for the option, how noise should be treated.

NOISE_ID - Static variable in class elki.evaluation.clustering.internal.PBMIndex.Par

Parameter for the option, how noise should be treated.

NOISE_ID - Static variable in class elki.evaluation.clustering.internal.Silhouette.Par

Parameter to treat noise as a single cluster.

NOISE_ID - Static variable in class elki.evaluation.clustering.internal.SquaredErrors.Par

Parameter to treat noise as a single cluster.

NOISE_ID - Static variable in class elki.evaluation.clustering.internal.VarianceRatioCriterion.Par

Parameter for the option, how noise should be treated.

noise1 - Variable in class elki.evaluation.clustering.ClusterContingencyTable

Noise flags

noise2 - Variable in class elki.evaluation.clustering.ClusterContingencyTable

Noise flags

noiseFlag - Variable in class elki.clustering.kmeans.KMeansMinusMinus

Create a noise cluster, otherwise assign to the nearest cluster.

noiseFlag - Variable in class elki.clustering.kmeans.KMeansMinusMinus.Par

Noise cluster flag.

noiseHandling - Variable in class elki.evaluation.clustering.internal.ConcordantPairsGammaTau

Option for noise handling.

noiseHandling - Variable in class elki.evaluation.clustering.internal.ConcordantPairsGammaTau.Par

Option, how noise should be treated.

noiseHandling - Variable in class elki.evaluation.clustering.internal.PBMIndex

Option for noise handling.

noiseHandling - Variable in class elki.evaluation.clustering.internal.PBMIndex.Par

Option, how noise should be treated.

NoiseHandling - Enum in elki.evaluation.clustering.internal

Options for handling noise in internal measures.

NoiseHandling() - Constructor for enum elki.evaluation.clustering.internal.NoiseHandling

noiseOption - Variable in class elki.evaluation.clustering.internal.CIndex

Option for noise handling.

noiseOption - Variable in class elki.evaluation.clustering.internal.CIndex.Par

Option, how noise should be treated.

noiseOption - Variable in class elki.evaluation.clustering.internal.ClusterRadius

Handling of Noise clusters

noiseOption - Variable in class elki.evaluation.clustering.internal.ClusterRadius.Par

Handling of noise clusters.

noiseOption - Variable in class elki.evaluation.clustering.internal.DaviesBouldinIndex

Option for noise handling.

noiseOption - Variable in class elki.evaluation.clustering.internal.DaviesBouldinIndex.Par

Option, how noise should be treated.

noiseOption - Variable in class elki.evaluation.clustering.internal.Silhouette

Option for noise handling.

noiseOption - Variable in class elki.evaluation.clustering.internal.Silhouette.Par

Noise handling

noiseOption - Variable in class elki.evaluation.clustering.internal.SimplifiedSilhouette

Option for noise handling.

noiseOption - Variable in class elki.evaluation.clustering.internal.SimplifiedSilhouette.Par

Option, how noise should be treated.

noiseOption - Variable in class elki.evaluation.clustering.internal.SquaredErrors

Handling of Noise clusters

noiseOption - Variable in class elki.evaluation.clustering.internal.SquaredErrors.Par

Handling of noise clusters.

noiseOption - Variable in class elki.evaluation.clustering.internal.VarianceRatioCriterion

Option for noise handling.

noiseOption - Variable in class elki.evaluation.clustering.internal.VarianceRatioCriterion.Par

Option, how noise should be treated.

noisepat - Variable in class elki.clustering.trivial.ByLabelClustering.Par

Pattern to recognize noise clusters by.

noisepattern - Variable in class elki.clustering.trivial.ByLabelClustering

Pattern to recognize noise clusters by.

noiseSpecialHandling - Variable in class elki.evaluation.clustering.EvaluateClustering

Apply special handling to noise "clusters".

noiseSpecialHandling - Variable in class elki.evaluation.clustering.EvaluateClustering.Par

Apply special handling to noise "clusters".

NOKEEPMED_ID - Static variable in class elki.clustering.kmedoids.CLARA.Par

Draw independent samples.

NOKEEPMED_ID - Static variable in class elki.clustering.kmedoids.FastCLARA.Par

Draw independent samples.

NOKEEPMED_ID - Static variable in class elki.clustering.kmedoids.FasterCLARA.Par

Draw independent samples.

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

Get the normalized information distance (normalized, small values are good).

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

Get the normalized variation of information (normalized, small values are good).

NOSIMPLIFY_ID - Static variable in class elki.clustering.hierarchical.extraction.AbstractCutDendrogram.Par

Disable the simplification that puts points into merge clusters.

NOT_SELECTED - Static variable in interface elki.clustering.biclustering.ChengAndChurch.CellVisitor

Different modes of operation.

npred - Variable in class elki.clustering.dbscan.GeneralizedDBSCAN.Instance

The neighborhood predicate

npred - Variable in class elki.clustering.dbscan.GeneralizedDBSCAN

The neighborhood predicate factory.

npred - Variable in class elki.clustering.dbscan.GeneralizedDBSCAN.Par

Neighborhood predicate.

npred - Variable in class elki.clustering.dbscan.parallel.ParallelGeneralizedDBSCAN.Instance

The neighborhood predicate

npred - Variable in class elki.clustering.dbscan.parallel.ParallelGeneralizedDBSCAN

The neighborhood predicate factory.

npred - Variable in class elki.clustering.dbscan.parallel.ParallelGeneralizedDBSCAN.Par

Neighborhood predicate.

npreds - Variable in class elki.clustering.dbscan.parallel.ParallelGeneralizedDBSCAN.Instance

Factory for neighbor predicates.

num - Variable in class elki.clustering.dbscan.util.Core

Cluster number

numberOfFeatureVectors() - Method in class elki.clustering.subspace.clique.CLIQUEUnit

Returns the number of feature vectors this unit contains.

numberOfFreeParameters(Relation<? extends NumberVector>, Clustering<? extends MeanModel>) - Static method in class elki.clustering.kmeans.quality.AbstractKMeansQualityMeasure

Compute the number of free parameters.

NumberVectorInstance(Relation<? extends NumberVector>, NumberVectorDistance<?>, RandomFactory) - Constructor for class elki.clustering.kmeans.initialization.KMeansPlusPlus.NumberVectorInstance

Constructor.

NumberVectorInstance(Relation<? extends NumberVector>, NumberVectorDistance<?>, RandomFactory) - Constructor for class elki.clustering.kmeans.initialization.Ostrovsky.NumberVectorInstance

Constructor.

numCl - Variable in class elki.clustering.hierarchical.extraction.ClustersWithNoiseExtraction

Minimum number of clusters.

numCl - Variable in class elki.clustering.hierarchical.extraction.ClustersWithNoiseExtraction.Par

Minimum number of clusters.

numclusters - Variable in class elki.evaluation.clustering.pairsegments.Segments

Number of Clusters for each clustering

numLeaves() - Method in class elki.index.tree.betula.CFTree

Get the number of leaves in the tree.

numlocal - Variable in class elki.clustering.kmedoids.CLARANS

Number of samples to draw (i.e. restarts).

numlocal - Variable in class elki.clustering.kmedoids.CLARANS.Par

Number of restarts to do.

numMerges() - Method in class elki.clustering.hierarchical.ClusterMergeHistory

Number of merges, usually n-1.

numPoints(Clustering<? extends MeanModel>) - Static method in class elki.clustering.kmeans.quality.AbstractKMeansQualityMeasure

Compute the number of points in a given set of clusters (which may be less than the complete data set for X-means!)

numsamples - Variable in class elki.clustering.kmedoids.CLARA

Number of samples to draw (i.e. iterations).

numsamples - Variable in class elki.clustering.kmedoids.CLARA.Par

Number of samples to draw (i.e. iterations).

numsamples - Variable in class elki.clustering.kmedoids.FastCLARA

Number of samples to draw (i.e. iterations).

numsamples - Variable in class elki.clustering.kmedoids.FastCLARA.Par

Number of samples to draw (i.e. iterations).

numsamples - Variable in class elki.clustering.kmedoids.FasterCLARA

Number of samples to draw (i.e. iterations).

numsamples - Variable in class elki.clustering.kmedoids.FasterCLARA.Par

Number of samples to draw (i.e. iterations).

NUMSAMPLES_ID - Static variable in class elki.clustering.kmedoids.CLARA.Par

The number of samples to run.

NUMSAMPLES_ID - Static variable in class elki.clustering.kmedoids.FastCLARA.Par

The number of samples to run.

NUMSAMPLES_ID - Static variable in class elki.clustering.kmedoids.FasterCLARA.Par

The number of samples to run.

numterms - Variable in class elki.datasource.parser.ClusteringVectorParser

Number of different terms observed.

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