| Package | Description | 
|---|---|
| de.lmu.ifi.dbs.elki.database.query.knn | Prepared queries for k nearest neighbor (kNN) queries. | 
| de.lmu.ifi.dbs.elki.index.preprocessed.knn | Indexes providing KNN and rKNN data. | 
| de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection | Visualizers for object selection based on 2D projections. | 
| Modifier and Type | Field and Description | 
|---|---|
| private AbstractMaterializeKNNPreprocessor<O,D,T> | PreprocessorKNNQuery. preprocessorThe last preprocessor result | 
| Modifier and Type | Method and Description | 
|---|---|
| AbstractMaterializeKNNPreprocessor<O,D,T> | PreprocessorKNNQuery. getPreprocessor()Get the preprocessor instance. | 
| Constructor and Description | 
|---|
| PreprocessorKNNQuery(Relation<O> database,
                    AbstractMaterializeKNNPreprocessor<O,D,T> preprocessor)Constructor. | 
| Modifier and Type | Class and Description | 
|---|---|
| class  | KNNJoinMaterializeKNNPreprocessor<V extends NumberVector<?>,D extends Distance<D>>Class to materialize the kNN using a spatial join on an R-tree. | 
| class  | MaterializeKNNAndRKNNPreprocessor<O,D extends Distance<D>>A preprocessor for annotation of the k nearest neighbors and the reverse k
 nearest neighbors (and their distances) to each database object. | 
| class  | MaterializeKNNPreprocessor<O,D extends Distance<D>>A preprocessor for annotation of the k nearest neighbors (and their
 distances) to each database object. | 
| class  | MetricalIndexApproximationMaterializeKNNPreprocessor<O extends NumberVector<?>,D extends Distance<D>,N extends Node<E>,E extends MTreeEntry<D>>A preprocessor for annotation of the k nearest neighbors (and their
 distances) to each database object. | 
| class  | PartitionApproximationMaterializeKNNPreprocessor<O,D extends Distance<D>>A preprocessor for annotation of the k nearest neighbors (and their
 distances) to each database object. | 
| class  | RandomSampleKNNPreprocessor<O,D extends Distance<D>>Class that computed the kNN only on a random sample. | 
| class  | SpatialApproximationMaterializeKNNPreprocessor<O extends NumberVector<?>,D extends Distance<D>,N extends SpatialNode<N,E>,E extends SpatialEntry>A preprocessor for annotation of the k nearest neighbors (and their
 distances) to each database object. | 
| Modifier and Type | Method and Description | 
|---|---|
| abstract AbstractMaterializeKNNPreprocessor<O,D,T> | AbstractMaterializeKNNPreprocessor.Factory. instantiate(Relation<O> relation) | 
| Modifier and Type | Field and Description | 
|---|---|
| private AbstractMaterializeKNNPreprocessor<? extends NumberVector<?>,D,?> | DistanceFunctionVisualization.Instance. resultThe selection result we work on | 
| Modifier and Type | Method and Description | 
|---|---|
| static double | DistanceFunctionVisualization. getLPNormP(AbstractMaterializeKNNPreprocessor<?,?,?> kNN)Get the "p" value of an Lp norm. | 
| static boolean | DistanceFunctionVisualization. isAngularDistance(AbstractMaterializeKNNPreprocessor<?,?,?> kNN)Test whether the given preprocessor used an angular distance function |