| Package | Description | 
|---|---|
| de.lmu.ifi.dbs.elki.algorithm | 
 Algorithms suitable as a task for the  
KDDTask main routine. | 
| de.lmu.ifi.dbs.elki.algorithm.clustering | 
 Clustering algorithms. 
 | 
| de.lmu.ifi.dbs.elki.database.query.distance | 
 Prepared queries for distances. 
 | 
| de.lmu.ifi.dbs.elki.distance.distancefunction | 
 Distance functions for use within ELKI. 
 | 
| de.lmu.ifi.dbs.elki.distance.distancefunction.colorhistogram | 
 Distance functions using correlations. 
 | 
| de.lmu.ifi.dbs.elki.distance.distancefunction.geo | 
 Geographic (earth) distance functions. 
 | 
| de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski | 
 Minkowski space L_p norms such as the popular Euclidean and Manhattan distances. 
 | 
| de.lmu.ifi.dbs.elki.distance.distancefunction.subspace | 
 Distance functions based on subspaces. 
 | 
| de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.query | 
 Queries on the R-Tree family of indexes: kNN and range queries. 
 | 
| Modifier and Type | Method and Description | 
|---|---|
private List<KNNHeap<D>> | 
KNNJoin.initHeaps(SpatialPrimitiveDistanceFunction<V,D> distFunction,
         N pr)
Initialize the heaps. 
 | 
private void | 
KNNJoin.processDataPagesOptimize(SpatialPrimitiveDistanceFunction<V,D> distFunction,
                        List<? extends KNNHeap<D>> pr_heaps,
                        List<? extends KNNHeap<D>> ps_heaps,
                        N pr,
                        N ps)
Processes the two data pages pr and ps and determines the k-nearest
 neighbors of pr in ps. 
 | 
| Modifier and Type | Method and Description | 
|---|---|
private void | 
DeLiClu.expandDirNodes(SpatialPrimitiveDistanceFunction<NV,D> distFunction,
              DeLiCluNode node1,
              DeLiCluNode node2)
Expands the specified directory nodes. 
 | 
private void | 
DeLiClu.expandLeafNodes(SpatialPrimitiveDistanceFunction<NV,D> distFunction,
               DeLiCluNode node1,
               DeLiCluNode node2,
               DataStore<KNNList<D>> knns)
Expands the specified leaf nodes. 
 | 
private void | 
DeLiClu.expandNodes(DeLiCluTree index,
           SpatialPrimitiveDistanceFunction<NV,D> distFunction,
           DeLiClu.SpatialObjectPair nodePair,
           DataStore<KNNList<D>> knns)
Expands the spatial nodes of the specified pair. 
 | 
private void | 
DeLiClu.reinsertExpanded(SpatialPrimitiveDistanceFunction<NV,D> distFunction,
                DeLiCluTree index,
                List<TreeIndexPathComponent<DeLiCluEntry>> path,
                DataStore<KNNList<D>> knns)
Reinserts the objects of the already expanded nodes. 
 | 
private void | 
DeLiClu.reinsertExpanded(SpatialPrimitiveDistanceFunction<NV,D> distFunction,
                DeLiCluTree index,
                List<TreeIndexPathComponent<DeLiCluEntry>> path,
                int pos,
                SpatialDirectoryEntry parentEntry,
                DataStore<KNNList<D>> knns)  | 
| Modifier and Type | Field and Description | 
|---|---|
protected SpatialPrimitiveDistanceFunction<? super V,D> | 
SpatialPrimitiveDistanceQuery.distanceFunction
The distance function we use. 
 | 
| Modifier and Type | Method and Description | 
|---|---|
SpatialPrimitiveDistanceFunction<? super V,D> | 
SpatialPrimitiveDistanceQuery.getDistanceFunction()  | 
SpatialPrimitiveDistanceFunction<? super V,D> | 
SpatialDistanceQuery.getDistanceFunction()
Get the inner distance function. 
 | 
| Constructor and Description | 
|---|
SpatialPrimitiveDistanceQuery(Relation<? extends V> relation,
                             SpatialPrimitiveDistanceFunction<? super V,D> distanceFunction)  | 
| Modifier and Type | Interface and Description | 
|---|---|
interface  | 
SpatialPrimitiveDoubleDistanceFunction<V extends SpatialComparable>
Interface combining spatial primitive distance functions with primitive
 number distance functions. 
 | 
| Modifier and Type | Class and Description | 
|---|---|
class  | 
AbstractSpatialDoubleDistanceFunction
Abstract base class for typical distance functions that allow
 rectangle-to-rectangle lower bounds. 
 | 
class  | 
AbstractSpatialDoubleDistanceNorm
Abstract base class for typical distance functions that allow
 rectangle-to-rectangle lower bounds. 
 | 
class  | 
ArcCosineDistanceFunction
Cosine distance function for feature vectors. 
 | 
class  | 
BrayCurtisDistanceFunction
Bray-Curtis distance function / Sørensen–Dice coefficient for continuous
 spaces. 
 | 
class  | 
CanberraDistanceFunction
Canberra distance function, a variation of Manhattan distance. 
 | 
class  | 
ClarkDistanceFunction
Clark distance function for vector spaces. 
 | 
class  | 
CosineDistanceFunction
Cosine distance function for feature vectors. 
 | 
class  | 
Kulczynski1DistanceFunction
Kulczynski similarity 1, in distance form. 
 | 
class  | 
LorentzianDistanceFunction
Lorentzian distance function for vector spaces. 
 | 
| Modifier and Type | Class and Description | 
|---|---|
class  | 
HistogramIntersectionDistanceFunction
Intersection distance for color histograms. 
 | 
| Modifier and Type | Class and Description | 
|---|---|
class  | 
DimensionSelectingLatLngDistanceFunction
Distance function for 2D vectors in Latitude, Longitude form. 
 | 
class  | 
LatLngDistanceFunction
Distance function for 2D vectors in Latitude, Longitude form. 
 | 
class  | 
LngLatDistanceFunction
Distance function for 2D vectors in Longitude, Latitude form. 
 | 
| Modifier and Type | Class and Description | 
|---|---|
class  | 
EuclideanDistanceFunction
Provides the Euclidean distance for FeatureVectors. 
 | 
class  | 
LPNormDistanceFunction
Provides a LP-Norm for FeatureVectors. 
 | 
class  | 
ManhattanDistanceFunction
Manhattan distance function to compute the Manhattan distance for a pair of
 FeatureVectors. 
 | 
class  | 
MaximumDistanceFunction
Maximum distance function to compute the Maximum distance for a pair of
 FeatureVectors. 
 | 
class  | 
MinimumDistanceFunction
Maximum distance function to compute the Minimum distance for a pair of
 FeatureVectors. 
 | 
class  | 
SquaredEuclideanDistanceFunction
Provides the squared Euclidean distance for FeatureVectors. 
 | 
class  | 
WeightedLPNormDistanceFunction
Weighted version of the Euclidean distance function. 
 | 
| Modifier and Type | Class and Description | 
|---|---|
class  | 
DimensionSelectingDistanceFunction
Provides a distance function that computes the distance between feature
 vectors as the absolute difference of their values in a specified dimension. 
 | 
class  | 
SubspaceEuclideanDistanceFunction
Provides a distance function that computes the Euclidean distance between
 feature vectors only in specified dimensions. 
 | 
class  | 
SubspaceLPNormDistanceFunction
Provides a distance function that computes the Euclidean distance between
 feature vectors only in specified dimensions. 
 | 
class  | 
SubspaceManhattanDistanceFunction
Provides a distance function that computes the Euclidean distance between
 feature vectors only in specified dimensions. 
 | 
| Modifier and Type | Field and Description | 
|---|---|
protected SpatialPrimitiveDistanceFunction<? super O,D> | 
GenericRStarTreeRangeQuery.distanceFunction
Spatial primitive distance function 
 | 
protected SpatialPrimitiveDistanceFunction<? super O,D> | 
GenericRStarTreeKNNQuery.distanceFunction
Spatial primitive distance function 
 |