de.lmu.ifi.dbs.elki.index.preprocessed.knn

Class SpacefillingKNNPreprocessor<O extends NumberVector>

java.lang.Object

de.lmu.ifi.dbs.elki.index.AbstractIndex<O>

de.lmu.ifi.dbs.elki.index.preprocessed.knn.SpacefillingKNNPreprocessor<O>

All Implemented Interfaces:

Index, KNNIndex<O>, Result

@Reference(authors="E. Schubert, A. Zimek, H.-P. Kriegel",
           title="Fast and Scalable Outlier Detection with Approximate Nearest Neighbor Ensembles",
           booktitle="Proc. 20th International Conference on Database Systems for Advanced Applications (DASFAA)",
           url="http://dx.doi.org/10.1007/978-3-319-18123-3_2")
public class SpacefillingKNNPreprocessor<O extends NumberVector>
extends AbstractIndex<O>
implements KNNIndex<O>

Compute the nearest neighbors approximatively using space filling curves. This version computes the data projections and stores, then queries this data on-demand. This usually needs less memory (except for very small neighborhood sizes k) than SpacefillingMaterializeKNNPreprocessor, but will also be slower. Reference:

E. Schubert, A. Zimek, H.-P. Kriegel
Fast and Scalable Outlier Detection with Approximate Nearest Neighbor Ensembles
Proc. 20th International Conference on Database Systems for Advanced Applications (DASFAA), Hanoi, Vietnam, 2015.

Author:

Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	SpacefillingKNNPreprocessor.Factory<V extends NumberVector> Index factory class
protected class	SpacefillingKNNPreprocessor.SpaceFillingKNNQuery KNN Query processor for space filling curves

Field Summary

Fields

Modifier and Type	Field and Description
(package private) List<SpatialSorter>	curvegen Spatial curve generators
(package private) List<List<SpatialPair<DBID,NumberVector>>>	curves Curve storage
private static Logging	LOG Class logger
(package private) Mean	mean Mean number of distance computations
(package private) int	odim Number of dimensions to use.
(package private) WritableDataStore<int[]>	positions Curve position storage
(package private) RandomProjectionFamily	proj Random projection family to use.
(package private) Random	random Random number generator.
(package private) int	variants Number of variants to generate for each curve
(package private) double	window Curve window size

Fields inherited from class de.lmu.ifi.dbs.elki.index.AbstractIndex

relation

Constructor Summary

Constructors

Constructor and Description
SpacefillingKNNPreprocessor(Relation<O> relation, List<SpatialSorter> curvegen, double window, int variants, int odim, RandomProjectionFamily proj, Random random) Constructor.

Method Summary

Methods

Modifier and Type	Method and Description
KNNQuery<O>	getKNNQuery(DistanceQuery<O> distanceQuery, Object... hints) Get a KNN query object for the given distance query and k.
String	getLongName() A "pretty" name for the result, for use in titles, captions and menus.
String	getShortName() A short name for the result, useful for file names.
void	initialize() Initialize the index.
void	logStatistics() Send statistics to the logger, if enabled.
protected void	preprocess()
static int[]	randomPermutation(int[] out, Random random) Perform a random permutation of the array, in-place.
static int[]	range(int start, int end) Initialize an integer value range.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

LOG

private static final Logging LOG

Class logger

curvegen

final List<SpatialSorter> curvegen

Spatial curve generators

window

final double window

Curve window size

variants

final int variants

Number of variants to generate for each curve

curves

List<List<SpatialPair<DBID,NumberVector>>> curves

Curve storage

positions

WritableDataStore<int[]> positions

Curve position storage

mean

Mean mean

Mean number of distance computations

odim

final int odim

Number of dimensions to use.

proj

RandomProjectionFamily proj

Random projection family to use.

random

Random random

Random number generator.

Constructor Detail

SpacefillingKNNPreprocessor

public SpacefillingKNNPreprocessor(Relation<O> relation,
                           List<SpatialSorter> curvegen,
                           double window,
                           int variants,
                           int odim,
                           RandomProjectionFamily proj,
                           Random random)

Constructor.

Parameters:

relation - Relation to index.

curvegen - Curve generators

window - Window multiplicator

variants - Number of curve variants to generate

odim - Number of dimensions to use -1 == all.

random - Random number generator

Method Detail

initialize

public void initialize()

Description copied from interface: Index

Initialize the index. For static indexes, this is the moment the index is bulk loaded.

Specified by:

initialize in interface Index

preprocess

protected void preprocess()

range

public static int[] range(int start,
          int end)

Initialize an integer value range.

Parameters:

start - Starting value

end - End value (exclusive)

Returns:

Array of integers start..end, excluding end.

randomPermutation

public static int[] randomPermutation(int[] out,
                      Random random)

Perform a random permutation of the array, in-place. Knuth / Fisher-Yates style shuffle

Parameters:

out - Prefilled output array.

random - Random generator.

Returns:

Same array.

getLongName

public String getLongName()

Description copied from interface: Result

A "pretty" name for the result, for use in titles, captions and menus.

Specified by:

getLongName in interface Result

Specified by:

getLongName in class AbstractIndex<O extends NumberVector>

Returns:

result name

getShortName

public String getShortName()

Description copied from interface: Result

A short name for the result, useful for file names.

Specified by:

getShortName in interface Result

Specified by:

getShortName in class AbstractIndex<O extends NumberVector>

Returns:

result name

logStatistics

public void logStatistics()

Description copied from interface: Index

Send statistics to the logger, if enabled. Note: you must have set the logging level appropriately before initializing the index! Otherwise, the index might not have collected the desired statistics.

Specified by:

logStatistics in interface Index

getKNNQuery

public KNNQuery<O> getKNNQuery(DistanceQuery<O> distanceQuery,
                      Object... hints)

Description copied from interface: KNNIndex

Get a KNN query object for the given distance query and k. This function MAY return null, when the given distance is not supported!

Specified by:

getKNNQuery in interface KNNIndex<O extends NumberVector>

Parameters:

distanceQuery - Distance query

hints - Hints for the optimizer

Returns:

KNN Query object or null