Uses of Interface
elki.database.ids.ArrayModifiableDBIDs

Packages that use ArrayModifiableDBIDs

Package	Description
elki.clustering	Clustering algorithms.
elki.clustering.correlation	Correlation clustering algorithms.
elki.clustering.dbscan	DBSCAN and its generalizations.
elki.clustering.em	Expectation-Maximization clustering algorithm for Gaussian Mixture Modeling (GMM).
elki.clustering.hierarchical	Hierarchical agglomerative clustering (HAC).
elki.clustering.kmeans	K-means clustering and variations.
elki.clustering.kmeans.initialization	Initialization strategies for k-means.
elki.clustering.kmedoids	K-medoids clustering (PAM).
elki.clustering.kmedoids.initialization
elki.clustering.optics	OPTICS family of clustering algorithms.
elki.clustering.silhouette	Silhouette clustering algorithms.
elki.clustering.subspace	Axis-parallel subspace clustering algorithms.
elki.clustering.svm
elki.database	ELKI database layer - loading, storing, indexing and accessing data.
elki.database.datastore.memory	Memory data store implementation for ELKI.
elki.database.ids	Database object identification and ID group handling API.
elki.database.ids.integer	Integer-based DBID implementation -- do not use directly - always use DBIDUtil.
elki.index.laesa	Linear Approximating and Eliminating Search Algorithm (LAESA).
elki.index.preprocessed.fastoptics	Preprocessed index used by the FastOPTICS algorithm.
elki.index.tree.betula	BETULA clustering by aggregating the data into cluster features.
elki.index.tree.metrical.covertree	Cover-tree variations.
elki.index.tree.spatial.kd	K-d-tree and variants.
elki.index.tree.spatial.kd.split
elki.itemsetmining	Algorithms for frequent itemset mining such as APRIORI.
elki.outlier.density	Density-based outlier detection algorithms.
elki.outlier.lof	LOF family of outlier detection algorithms.
elki.result	Result types, representation and handling.
elki.result.outlier	Outlier result classes.
elki.similarity.kernel	Kernel functions.
elki.svm.data
elki.visualization.gui	Package to provide a visualization GUI.
tutorial.clustering	Classes from the tutorial on implementing a custom k-means variation.

Uses of ArrayModifiableDBIDs in elki.clustering

Methods in elki.clustering that return ArrayModifiableDBIDs

Modifier and Type	Method	Description
protected ArrayModifiableDBIDs	SNNClustering.findSNNNeighbors(SimilarityQuery<O> snnInstance, DBIDRef queryObject)	Returns the shared nearest neighbors of the specified query object in the given database.
static ArrayModifiableDBIDs[]	ClusteringAlgorithmUtil.partitionsFromIntegerLabels(DBIDs ids, IntegerDataStore assignment, int k)	Collect clusters from their [0;k-1] integer labels.

Uses of ArrayModifiableDBIDs in elki.clustering.correlation

Fields in elki.clustering.correlation declared as ArrayModifiableDBIDs

Modifier and Type	Field	Description
private ArrayModifiableDBIDs	HiCO.Instance.clusterOrder	Cluster order.
private ArrayModifiableDBIDs	HiCO.Instance.tmpIds	Temporary ids.

Uses of ArrayModifiableDBIDs in elki.clustering.dbscan

Methods in elki.clustering.dbscan with parameters of type ArrayModifiableDBIDs

Modifier and Type	Method	Description
protected void	DBSCAN.Instance.expandCluster(DBIDRef startObjectID, ArrayModifiableDBIDs seeds)	DBSCAN-function expandCluster.
protected int	GeneralizedDBSCAN.Instance.expandCluster(DBIDRef seed, int clusterid, WritableIntegerDataStore clusterids, T neighbors, ArrayModifiableDBIDs activeSet, FiniteProgress progress)	Set-based expand cluster implementation.
protected int	GriDBSCAN.Instance.expandCluster(DBIDRef seed, int clusterid, WritableIntegerDataStore clusterids, ModifiableDoubleDBIDList neighbors, ArrayModifiableDBIDs activeSet, RangeSearcher<DBIDRef> rq, FiniteProgress pprog)	Set-based expand cluster implementation.
protected int	GeneralizedDBSCAN.Instance.processCorePoint(DBIDRef seed, T newneighbors, int clusterid, WritableIntegerDataStore clusterids, ArrayModifiableDBIDs activeSet)	Process a single core point.
protected int	GriDBSCAN.Instance.processCorePoint(DBIDRef seed, DoubleDBIDList newneighbors, int clusterid, WritableIntegerDataStore clusterids, ArrayModifiableDBIDs activeSet)	Process a single core point.
private void	DBSCAN.Instance.processNeighbors(DoubleDBIDList neighbors, ModifiableDBIDs currentCluster, ArrayModifiableDBIDs seeds)	Process a single core point.
private int	GriDBSCAN.Instance.runDBSCANOnCell(DBIDs cellids, Relation<V> relation, ModifiableDoubleDBIDList neighbors, ArrayModifiableDBIDs activeSet, int clusterid)

Uses of ArrayModifiableDBIDs in elki.clustering.em

Fields in elki.clustering.em declared as ArrayModifiableDBIDs

Modifier and Type	Field	Description
protected ArrayModifiableDBIDs	KDTreeEM.sorted	kd-tree object order

Constructors in elki.clustering.em with parameters of type ArrayModifiableDBIDs

Constructor	Description
KDTree(Relation<? extends NumberVector> relation, ArrayModifiableDBIDs sorted, int left, int right, double[] dimWidth, double mbw)	Constructor for a KDTree with statistics needed for KDTreeEM calculation.

Uses of ArrayModifiableDBIDs in elki.clustering.hierarchical

Fields in elki.clustering.hierarchical declared as ArrayModifiableDBIDs

Modifier and Type	Field	Description
protected ArrayModifiableDBIDs	ClusterMergeHistoryBuilder.prototypes	Prototype storage, may be null.

Methods in elki.clustering.hierarchical with parameters of type ArrayModifiableDBIDs

Modifier and Type	Method	Description
protected static <O> ClusterDistanceMatrix	MiniMax.initializeMatrices(ArrayDBIDs ids, ArrayModifiableDBIDs prots, DistanceQuery<O> dq)	Initializes the inter-cluster distance matrix of possible merges

Uses of ArrayModifiableDBIDs in elki.clustering.kmeans

Fields in elki.clustering.kmeans declared as ArrayModifiableDBIDs

Modifier and Type	Field	Description
protected ArrayModifiableDBIDs	KDTreePruningKMeans.Instance.sorted	The tree stored as ArrayModifiableDBIDs

Uses of ArrayModifiableDBIDs in elki.clustering.kmeans.initialization

Methods in elki.clustering.kmeans.initialization with parameters of type ArrayModifiableDBIDs

Modifier and Type	Method	Description
protected void	KMeansPlusPlus.MedoidsInstance.chooseRemaining(int k, ArrayModifiableDBIDs means, double weightsum)	Choose remaining means, weighted by distance.

Uses of ArrayModifiableDBIDs in elki.clustering.kmedoids

Fields in elki.clustering.kmedoids declared as ArrayModifiableDBIDs

Modifier and Type	Field	Description
(package private) ArrayModifiableDBIDs	CLARANS.Assignment.medoids	Medoids

Methods in elki.clustering.kmedoids that return ArrayModifiableDBIDs

Modifier and Type	Method	Description
protected ArrayModifiableDBIDs	PAM.initialMedoids(DistanceQuery<? super O> distQ, DBIDs ids, int k)	Choose the initial medoids.

Methods in elki.clustering.kmedoids with parameters of type ArrayModifiableDBIDs

Modifier and Type	Method	Description
protected double	SingleAssignmentKMedoids.Instance.assignToNearestCluster(ArrayModifiableDBIDs means)	Assign each object to the nearest cluster, return the cost.
protected void	FastPAM.Instance.findBestSwaps(DBIDArrayIter m, ArrayModifiableDBIDs bestids, double[] best, double[] cost, double[] pcost)	Find the best swaps.
protected double	EagerPAM.Instance.run(ArrayModifiableDBIDs medoids, int maxiter)	Run the EagerPAM optimization phase.
protected double	FasterPAM.Instance.run(ArrayModifiableDBIDs medoids, int maxiter)	Run the PAM optimization phase.
protected double	FastPAM.Instance.run(ArrayModifiableDBIDs medoids, int maxiter)	Run the PAM optimization phase.
protected double	FastPAM1.Instance.run(ArrayModifiableDBIDs medoids, int maxiter)	Run the FastPAM optimization phase.
protected double	PAM.Instance.run(ArrayModifiableDBIDs medoids, int maxiter)	Run the PAM optimization phase.
protected double	ReynoldsPAM.Instance.run(ArrayModifiableDBIDs medoids, int maxiter)	Run the PAM optimization phase.
protected double	SingleAssignmentKMedoids.Instance.run(ArrayModifiableDBIDs medoids)	Run the PAM optimization phase.
protected void	FastPAM1.Instance.updateAssignment(ArrayModifiableDBIDs medoids, DBIDArrayIter miter, DBIDRef h, int m)	Update an existing cluster assignment.
protected static Clustering<MedoidModel>	PAM.wrapResult(DBIDs ids, WritableIntegerDataStore assignment, ArrayModifiableDBIDs medoids, java.lang.String name)	Wrap the clustering result.

Uses of ArrayModifiableDBIDs in elki.clustering.kmedoids.initialization

Methods in elki.clustering.kmedoids.initialization with parameters of type ArrayModifiableDBIDs

Modifier and Type	Method	Description
private static void	LAB.shuffle(ArrayModifiableDBIDs ids, int ssize, int end, java.util.Random random)	Partial Fisher-Yates shuffle.

Uses of ArrayModifiableDBIDs in elki.clustering.optics

Fields in elki.clustering.optics declared as ArrayModifiableDBIDs

Modifier and Type	Field	Description
protected ArrayModifiableDBIDs	GeneralizedOPTICS.Instance.candidates	Current list of candidates.
(package private) ArrayModifiableDBIDs	OPTICSList.Instance.candidates	Current list of candidates.
(package private) ArrayModifiableDBIDs	ClusterOrder.ids	Cluster order.

Methods in elki.clustering.optics that return ArrayModifiableDBIDs

Modifier and Type	Method	Description
ArrayModifiableDBIDs	ClusterOrder.order(DBIDs ids)	Use the cluster order to sort the given collection ids.

Methods in elki.clustering.optics with parameters of type ArrayModifiableDBIDs

Modifier and Type	Method	Description
void	OPTICSList.Instance.findBest(ArrayModifiableDBIDs candidates, DBIDArrayMIter it, DBIDVar out)	Find the minimum in the candidates array.

Constructors in elki.clustering.optics with parameters of type ArrayModifiableDBIDs

Constructor	Description
ClusterOrder(ArrayModifiableDBIDs ids, WritableDoubleDataStore reachability, WritableDBIDDataStore predecessor)	Constructor
CorrelationClusterOrder(ArrayModifiableDBIDs ids, WritableDoubleDataStore reachability, WritableDBIDDataStore predecessor, WritableIntegerDataStore corrdim)	Constructor.

Uses of ArrayModifiableDBIDs in elki.clustering.silhouette

Methods in elki.clustering.silhouette with parameters of type ArrayModifiableDBIDs

Modifier and Type	Method	Description
protected double	FasterMSC.Instance.run(ArrayModifiableDBIDs medoids, int maxiter)	Run the FasterMSC optimization phase.
protected double	FasterMSC.Instance2.run(ArrayModifiableDBIDs medoids, int maxiter)	Run the FasterMSC optimization phase.
protected double	FastMSC.Instance.run(ArrayModifiableDBIDs medoids, int maxiter)	Run the FastMSC optimization phase.
protected double	FastMSC.Instance2.run(ArrayModifiableDBIDs medoids, int maxiter)	Run the FastMSC optimization phase.
protected double	PAMMEDSIL.Instance.run(ArrayModifiableDBIDs medoids, int maxiter)	Run the PAMMEDSIL optimization phase.
protected double	PAMSIL.Instance.run(ArrayModifiableDBIDs medoids, int maxiter)	Run the PAMSIL optimization phase.

Uses of ArrayModifiableDBIDs in elki.clustering.subspace

Fields in elki.clustering.subspace declared as ArrayModifiableDBIDs

Modifier and Type	Field	Description
private ArrayModifiableDBIDs	DiSH.Instance.clusterOrder	Cluster order.
private ArrayModifiableDBIDs	HiSC.Instance.clusterOrder	Cluster order.
private ArrayModifiableDBIDs	DiSH.Instance.tmpIds	Temporary ids.

Methods in elki.clustering.subspace that return types with arguments of type ArrayModifiableDBIDs

Modifier and Type	Method	Description
private it.unimi.dsi.fastutil.objects.Object2ObjectOpenCustomHashMap<long[],java.util.List<ArrayModifiableDBIDs>>	DiSH.extractClusters(Relation<? extends NumberVector> relation, DiSH.DiSHClusterOrder clusterOrder)	Extracts the clusters from the cluster order.
private Pair<long[],ArrayModifiableDBIDs>	DiSH.findParent(Relation<? extends NumberVector> relation, Pair<long[],ArrayModifiableDBIDs> child, it.unimi.dsi.fastutil.objects.Object2ObjectMap<long[],java.util.List<ArrayModifiableDBIDs>> clustersMap)	Returns the parent of the specified cluster

Methods in elki.clustering.subspace with parameters of type ArrayModifiableDBIDs

Modifier and Type	Method	Description
protected DBIDs	DOC.findNeighbors(DBIDRef q, long[] nD, ArrayModifiableDBIDs S, Relation<? extends NumberVector> relation)	Find the neighbors of point q in the given subspace
protected Cluster<SubspaceModel>	DOC.runDOC(Relation<? extends NumberVector> relation, ArrayModifiableDBIDs S, int d, int n, int m, int r, int minClusterSize)	Performs a single run of DOC, finding a single cluster.
protected Cluster<SubspaceModel>	FastDOC.runDOC(Relation<? extends NumberVector> relation, ArrayModifiableDBIDs S, int d, int n, int m, int r, int minClusterSize)	Performs a single run of FastDOC, finding a single cluster.

Method parameters in elki.clustering.subspace with type arguments of type ArrayModifiableDBIDs

Modifier and Type	Method	Description
private void	DiSH.checkClusters(Relation<? extends NumberVector> relation, it.unimi.dsi.fastutil.objects.Object2ObjectMap<long[],java.util.List<ArrayModifiableDBIDs>> clustersMap)	Removes the clusters with size < minpts from the cluster map and adds them to their parents.
private Pair<long[],ArrayModifiableDBIDs>	DiSH.findParent(Relation<? extends NumberVector> relation, Pair<long[],ArrayModifiableDBIDs> child, it.unimi.dsi.fastutil.objects.Object2ObjectMap<long[],java.util.List<ArrayModifiableDBIDs>> clustersMap)	Returns the parent of the specified cluster
private Pair<long[],ArrayModifiableDBIDs>	DiSH.findParent(Relation<? extends NumberVector> relation, Pair<long[],ArrayModifiableDBIDs> child, it.unimi.dsi.fastutil.objects.Object2ObjectMap<long[],java.util.List<ArrayModifiableDBIDs>> clustersMap)	Returns the parent of the specified cluster
private void	DiSH.logClusterSizes(java.lang.String m, int dimensionality, it.unimi.dsi.fastutil.objects.Object2ObjectOpenCustomHashMap<long[],java.util.List<ArrayModifiableDBIDs>> clustersMap)	Log cluster sizes in verbose mode.
private java.util.List<Cluster<SubspaceModel>>	DiSH.sortClusters(Relation<? extends NumberVector> relation, it.unimi.dsi.fastutil.objects.Object2ObjectMap<long[],java.util.List<ArrayModifiableDBIDs>> clustersMap)	Returns a sorted list of the clusters w.r.t. the subspace dimensionality in descending order.

Constructors in elki.clustering.subspace with parameters of type ArrayModifiableDBIDs

Constructor	Description
DiSHClusterOrder(ArrayModifiableDBIDs ids, WritableDoubleDataStore reachability, WritableDBIDDataStore predecessor, WritableIntegerDataStore corrdim, WritableDataStore<long[]> commonPreferenceVectors)	Constructor.

Uses of ArrayModifiableDBIDs in elki.clustering.svm

Methods in elki.clustering.svm that return types with arguments of type ArrayModifiableDBIDs

Modifier and Type	Method	Description
private java.util.ArrayList<ArrayModifiableDBIDs>	SupportVectorClustering.collectClusters(StaticDBIDs sids, UnionFind uf)

Uses of ArrayModifiableDBIDs in elki.database

Methods in elki.database that return ArrayModifiableDBIDs

Modifier and Type	Method	Description
static ArrayModifiableDBIDs	DatabaseUtil.getObjectsByLabelMatch(Database database, java.util.regex.Pattern name_pattern)	Find object by matching their labels.

Uses of ArrayModifiableDBIDs in elki.database.datastore.memory

Fields in elki.database.datastore.memory declared as ArrayModifiableDBIDs

Modifier and Type	Field	Description
private ArrayModifiableDBIDs	ArrayDBIDStore.data	Data array

Uses of ArrayModifiableDBIDs in elki.database.ids

Methods in elki.database.ids that return ArrayModifiableDBIDs

Modifier and Type	Method	Description
ArrayModifiableDBIDs	ArrayModifiableDBIDs.clear()
ArrayModifiableDBIDs	DBIDFactory.newArray()	Make a new (modifiable) array of DBIDs.
ArrayModifiableDBIDs	DBIDFactory.newArray(int size)	Make a new (modifiable) array of DBIDs.
ArrayModifiableDBIDs	DBIDFactory.newArray(DBIDs existing)	Make a new (modifiable) array of DBIDs.
static ArrayModifiableDBIDs	DBIDUtil.newArray()	Make a new (modifiable) array of DBIDs.
static ArrayModifiableDBIDs	DBIDUtil.newArray(int size)	Make a new (modifiable) array of DBIDs.
static ArrayModifiableDBIDs	DBIDUtil.newArray(DBIDs existing)	Make a new (modifiable) array of DBIDs.

Methods in elki.database.ids with parameters of type ArrayModifiableDBIDs

Modifier and Type	Method	Description
private static void	QuickSelectDBIDs.insertionSort(ArrayModifiableDBIDs data, java.util.Comparator<? super DBIDRef> comparator, int start, int end, DBIDArrayIter iter1, DBIDArrayIter iter2)	Sort a small array using repetitive insertion sort.
static int	QuickSelectDBIDs.median(ArrayModifiableDBIDs data, java.util.Comparator<? super DBIDRef> comparator)	Compute the median of an array efficiently using the QuickSelect method.
static int	QuickSelectDBIDs.median(ArrayModifiableDBIDs data, java.util.Comparator<? super DBIDRef> comparator, int begin, int end)	Compute the median of an array efficiently using the QuickSelect method.
static int	QuickSelectDBIDs.quantile(ArrayModifiableDBIDs data, java.util.Comparator<? super DBIDRef> comparator, double quant)	Compute the median of an array efficiently using the QuickSelect method.
static int	QuickSelectDBIDs.quantile(ArrayModifiableDBIDs data, java.util.Comparator<? super DBIDRef> comparator, int begin, int end, double quant)	Compute the median of an array efficiently using the QuickSelect method.
static void	QuickSelectDBIDs.quickSelect(ArrayModifiableDBIDs data, java.util.Comparator<? super DBIDRef> comparator, int rank)	QuickSelect is essentially quicksort, except that we only "sort" that half of the array that we are interested in.
static void	QuickSelectDBIDs.quickSelect(ArrayModifiableDBIDs data, java.util.Comparator<? super DBIDRef> comparator, int start, int end, int rank)	QuickSelect is essentially quicksort, except that we only "sort" that half of the array that we are interested in.
static void	DBIDUtil.randomShuffle(ArrayModifiableDBIDs ids, RandomFactory rnd)	Produce a random shuffling of the given DBID array.
static void	DBIDUtil.randomShuffle(ArrayModifiableDBIDs ids, java.util.Random random)	Produce a random shuffling of the given DBID array.
static void	DBIDUtil.randomShuffle(ArrayModifiableDBIDs ids, java.util.Random random, int limit)	Produce a random shuffling of the given DBID array.

Uses of ArrayModifiableDBIDs in elki.database.ids.integer

Classes in elki.database.ids.integer that implement ArrayModifiableDBIDs

Modifier and Type	Class	Description
(package private) class	ArrayModifiableIntegerDBIDs	Class using a primitive int[] array as storage.

Methods in elki.database.ids.integer that return ArrayModifiableDBIDs

Modifier and Type	Method	Description
ArrayModifiableDBIDs	AbstractIntegerDBIDFactory.newArray()
ArrayModifiableDBIDs	AbstractIntegerDBIDFactory.newArray(int size)
ArrayModifiableDBIDs	AbstractIntegerDBIDFactory.newArray(DBIDs existing)

Uses of ArrayModifiableDBIDs in elki.index.laesa

Fields in elki.index.laesa declared as ArrayModifiableDBIDs

Modifier and Type	Field	Description
(package private) ArrayModifiableDBIDs	LAESA.refp	Reference points

Uses of ArrayModifiableDBIDs in elki.index.preprocessed.fastoptics

Methods in elki.index.preprocessed.fastoptics with parameters of type ArrayModifiableDBIDs

Modifier and Type	Method	Description
int	RandomProjectedNeighborsAndDensities.splitByDistance(ArrayModifiableDBIDs ind, int begin, int end, DoubleDataStore tpro, java.util.Random rand)	Split the data set by distances.
int	RandomProjectedNeighborsAndDensities.splitRandomly(ArrayModifiableDBIDs ind, int begin, int end, DoubleDataStore tpro, java.util.Random rand)	Split the data set randomly.
void	RandomProjectedNeighborsAndDensities.splitupNoSort(ArrayModifiableDBIDs ind, int begin, int end, int dim, java.util.Random rand)	Recursively splits entire point set until the set is below a threshold

Uses of ArrayModifiableDBIDs in elki.index.tree.betula

Fields in elki.index.tree.betula with type parameters of type ArrayModifiableDBIDs

Modifier and Type	Field	Description
(package private) java.util.Map<ClusterFeature,ArrayModifiableDBIDs>	CFTree.idmap	Stored leaf entry to dbid relation

Uses of ArrayModifiableDBIDs in elki.index.tree.metrical.covertree

Fields in elki.index.tree.metrical.covertree declared as ArrayModifiableDBIDs

Modifier and Type	Field	Description
(package private) ArrayModifiableDBIDs	SimplifiedCoverTree.Node.singletons	Objects in this node.

Uses of ArrayModifiableDBIDs in elki.index.tree.spatial.kd

Fields in elki.index.tree.spatial.kd declared as ArrayModifiableDBIDs

Modifier and Type	Field	Description
protected ArrayModifiableDBIDs	MinimalisticMemoryKDTree.sorted	The actual "tree" as a sorted array.

Methods in elki.index.tree.spatial.kd with parameters of type ArrayModifiableDBIDs

Modifier and Type	Method	Description
java.lang.Object	MemoryKDTree.buildTree(Relation<? extends NumberVector> relation, int left, int right, ArrayModifiableDBIDs sorted, DBIDArrayMIter iter, VectorUtil.SortDBIDsBySingleDimension comp)	Build the k-d tree.

Uses of ArrayModifiableDBIDs in elki.index.tree.spatial.kd.split

Methods in elki.index.tree.spatial.kd.split with parameters of type ArrayModifiableDBIDs

Modifier and Type	Method	Description
SplitStrategy.Info	BoundedMidpointSplit.findSplit(Relation<? extends NumberVector> relation, int dims, ArrayModifiableDBIDs sorted, DBIDArrayMIter iter, int left, int right, VectorUtil.SortDBIDsBySingleDimension comp)
SplitStrategy.Info	LeastOneDimSSQSplit.findSplit(Relation<? extends NumberVector> relation, int dims, ArrayModifiableDBIDs sorted, DBIDArrayMIter iter, int left, int right, VectorUtil.SortDBIDsBySingleDimension comp)
SplitStrategy.Info	LeastSSQSplit.findSplit(Relation<? extends NumberVector> relation, int dims, ArrayModifiableDBIDs sorted, DBIDArrayMIter iter, int left, int right, VectorUtil.SortDBIDsBySingleDimension comp)
SplitStrategy.Info	MeanVarianceSplit.findSplit(Relation<? extends NumberVector> relation, int dims, ArrayModifiableDBIDs sorted, DBIDArrayMIter iter, int left, int right, VectorUtil.SortDBIDsBySingleDimension comp)
SplitStrategy.Info	MedianSplit.findSplit(Relation<? extends NumberVector> relation, int dims, ArrayModifiableDBIDs sorted, DBIDArrayMIter iter, int left, int right, VectorUtil.SortDBIDsBySingleDimension comp)
SplitStrategy.Info	MedianVarianceSplit.findSplit(Relation<? extends NumberVector> relation, int dims, ArrayModifiableDBIDs sorted, DBIDArrayMIter iter, int left, int right, VectorUtil.SortDBIDsBySingleDimension comp)
SplitStrategy.Info	MidpointSplit.findSplit(Relation<? extends NumberVector> relation, int dims, ArrayModifiableDBIDs sorted, DBIDArrayMIter iter, int left, int right, VectorUtil.SortDBIDsBySingleDimension comp)
SplitStrategy.Info	SplitStrategy.findSplit(Relation<? extends NumberVector> relation, int dims, ArrayModifiableDBIDs sorted, DBIDArrayMIter iter, int left, int right, VectorUtil.SortDBIDsBySingleDimension comp)	Build the k-d-tree using midpoint splitting.
(package private) static int	SplitStrategy.Util.pivot(Relation<? extends NumberVector> relation, ArrayModifiableDBIDs sorted, DBIDArrayMIter iter, int dim, int left, int right, double mid)	Pivot an interval.

Uses of ArrayModifiableDBIDs in elki.itemsetmining

Methods in elki.itemsetmining with parameters of type ArrayModifiableDBIDs

Modifier and Type	Method	Description
protected java.util.List<SparseItemset>	APRIORI.buildFrequentTwoItemsets(java.util.List<OneItemset> oneitems, Relation<BitVector> relation, int dim, int needed, DBIDs ids, ArrayModifiableDBIDs survivors)	Build the 2-itemsets.
protected java.util.List<? extends Itemset>	APRIORI.frequentItemsets(java.util.List<? extends Itemset> candidates, Relation<BitVector> relation, int needed, DBIDs ids, ArrayModifiableDBIDs survivors, int length)	Returns the frequent BitSets out of the given BitSets with respect to the given database.
protected java.util.List<SparseItemset>	APRIORI.frequentItemsetsSparse(java.util.List<SparseItemset> candidates, Relation<BitVector> relation, int needed, DBIDs ids, ArrayModifiableDBIDs survivors, int length)	Returns the frequent BitSets out of the given BitSets with respect to the given database.

Uses of ArrayModifiableDBIDs in elki.outlier.density

Fields in elki.outlier.density declared as ArrayModifiableDBIDs

Modifier and Type	Field	Description
(package private) ArrayModifiableDBIDs	IsolationForest.ForestBuilder.ids	Array of current candidates
(package private) ArrayModifiableDBIDs	HySortOD.Hypercube.instances	Holds a set of instances within the hypercube.

Uses of ArrayModifiableDBIDs in elki.outlier.lof

Methods in elki.outlier.lof with parameters of type ArrayModifiableDBIDs

Modifier and Type	Method	Description
private void	ALOCI.ALOCIQuadTree.bulkLoad(double[] lmin, double[] lmax, java.util.List<ALOCI.Node> children, ArrayModifiableDBIDs ids, int start, int end, int dim, int level, int code)	Bulk load the tree

Uses of ArrayModifiableDBIDs in elki.result

Methods in elki.result that return ArrayModifiableDBIDs

Modifier and Type	Method	Description
ArrayModifiableDBIDs	OrderingResult.order(DBIDs ids)	Sort the given ids according to this ordering and return an iterator.

Uses of ArrayModifiableDBIDs in elki.result.outlier

Methods in elki.result.outlier that return ArrayModifiableDBIDs

Modifier and Type	Method	Description
ArrayModifiableDBIDs	OrderingFromRelation.order(DBIDs ids)

Uses of ArrayModifiableDBIDs in elki.similarity.kernel

Fields in elki.similarity.kernel declared as ArrayModifiableDBIDs

Modifier and Type	Field	Description
(package private) ArrayModifiableDBIDs	KernelMatrix.SortedArrayMap.ids

Uses of ArrayModifiableDBIDs in elki.svm.data

Fields in elki.svm.data declared as ArrayModifiableDBIDs

Modifier and Type	Field	Description
(package private) ArrayModifiableDBIDs	SimilarityQueryAdapter.ids	Object ids to process.

Uses of ArrayModifiableDBIDs in elki.visualization.gui

Fields in elki.visualization.gui declared as ArrayModifiableDBIDs

Modifier and Type	Field	Description
(package private) ArrayModifiableDBIDs	SelectionTableWindow.dbids	The DBIDs to display

Uses of ArrayModifiableDBIDs in tutorial.clustering

Methods in tutorial.clustering that return ArrayModifiableDBIDs

Modifier and Type	Method	Description
protected ArrayModifiableDBIDs	SameSizeKMeans.initialAssignment(java.util.List<ModifiableDBIDs> clusters, WritableDataStore<SameSizeKMeans.Meta> metas, DBIDs ids)

Methods in tutorial.clustering with parameters of type ArrayModifiableDBIDs

Modifier and Type	Method	Description
protected double[][]	SameSizeKMeans.refineResult(Relation<V> relation, double[][] means, java.util.List<ModifiableDBIDs> clusters, WritableDataStore<SameSizeKMeans.Meta> metas, ArrayModifiableDBIDs tids)	Perform k-means style iterations to improve the clustering result.