weka.core.neighboursearch

Class CoverTree

java.lang.Object

weka.core.neighboursearch.NearestNeighbourSearch

weka.core.neighboursearch.CoverTree

All Implemented Interfaces:

Serializable, AdditionalMeasureProducer, OptionHandler, RevisionHandler, TechnicalInformationHandler

public class CoverTree
extends NearestNeighbourSearch
implements TechnicalInformationHandler

Class implementing the CoverTree datastructure.
The class is very much a translation of the c source code made available by the authors.

For more information and original source code see:

Alina Beygelzimer, Sham Kakade, John Langford: Cover trees for nearest neighbor. In: ICML'06: Proceedings of the 23rd international conference on Machine learning, New York, NY, USA, 97-104, 2006.

BibTeX:

 @inproceedings{Beygelzimer2006,
    address = {New York, NY, USA},
    author = {Alina Beygelzimer and Sham Kakade and John Langford},
    booktitle = {ICML'06: Proceedings of the 23rd international conference on Machine learning},
    pages = {97-104},
    publisher = {ACM Press},
    title = {Cover trees for nearest neighbor},
    year = {2006},
    location = {Pittsburgh, Pennsylvania},
    HTTP = {http://hunch.net/\~jl/projects/cover_tree/cover_tree.html}
 }
 

Valid options are:

 -B <value>
  Set base of the expansion constant
  (default = 1.3).
 

Version:

$Revision: 10203 $

Author:

Alina Beygelzimer (original C++ code), Sham Kakade (original C++ code), John Langford (original C++ code), Ashraf M. Kibriya (amk14[at-the-rate]cs[dot]waikato[dot]ac[dot]nz) (Java port)

See Also:

Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
class	CoverTree.CoverTreeNode class representing a node of the cover tree.

Constructor Summary

Constructors

Constructor and Description
CoverTree() default constructor.

Method Summary

Methods

Modifier and Type	Method and Description
void	addInstanceInfo(Instance ins) Adds the given instance info.
String	baseTipText() Returns the tip text for this property.
Enumeration<String>	enumerateMeasures() Returns an enumeration of the additional measure names.
double	getBase() Returns the base in use for expansion constant.
double[]	getDistances() Returns the distances of the (k)-NN(s) found earlier by kNearestNeighbours()/nearestNeighbour().
double	getMeasure(String additionalMeasureName) Returns the value of the named measure.
String[]	getOptions() Gets the current settings of KDtree.
String	getRevision() Returns the revision string.
TechnicalInformation	getTechnicalInformation() Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
String	globalInfo() Returns a string describing this nearest neighbour search algorithm.
Instances	kNearestNeighbours(Instance target, int k) Returns k-NNs of a given target instance, from among the previously supplied training instances (supplied through setInstances method) P.S.: May return more than k-NNs if more one instances have the same distance to the target as the kth NN.
Enumeration<Option>	listOptions() Returns an enumeration describing the available options.
static void	main(String[] args) Method for testing the class from command line.
double	measureMaxDepth() Returns the depth of the tree.
double	measureNumLeaves() Returns the number of leaves.
double	measureTreeSize() Returns the size of the tree.
Instance	nearestNeighbour(Instance target) Returns the NN instance of a given target instance, from among the previously supplied training instances.
void	setBase(double b) Sets the base to use for expansion constant.
void	setDistanceFunction(DistanceFunction df) Sets the distance function to use for nearest neighbour search.
void	setInstances(Instances instances) Builds the Cover Tree on the given set of instances.
void	setOptions(String[] options) Parses a given list of options.
void	update(Instance ins) Adds an instance to the cover tree.

Methods inherited from class weka.core.neighboursearch.NearestNeighbourSearch

combSort11, distanceFunctionTipText, getDistanceFunction, getInstances, getMeasurePerformance, getPerformanceStats, measurePerformanceTipText, quickSort, setMeasurePerformance

Methods inherited from class java.lang.Object

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

Constructor Detail

CoverTree

public CoverTree()

default constructor.

Method Detail

globalInfo

public String globalInfo()

Returns a string describing this nearest neighbour search algorithm.

Overrides:

globalInfo in class NearestNeighbourSearch

Returns:

a description of the algorithm for displaying in the explorer/experimenter gui

getTechnicalInformation

public TechnicalInformation getTechnicalInformation()

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

Specified by:

getTechnicalInformation in interface TechnicalInformationHandler

Returns:

the technical information about this class

listOptions

public Enumeration<Option> listOptions()

Returns an enumeration describing the available options.

Specified by:

listOptions in interface OptionHandler

Overrides:

listOptions in class NearestNeighbourSearch

Returns:

an enumeration of all the available options.

setOptions

public void setOptions(String[] options)
                throws Exception

Parses a given list of options.

Valid options are:

 -B <value>
  Set base of the expansion constant
  (default = 1.3).
 

Specified by:

setOptions in interface OptionHandler

Overrides:

setOptions in class NearestNeighbourSearch

Parameters:

options - the list of options as an array of strings

Throws:

Exception - if an option is not supported

getOptions

public String[] getOptions()

Gets the current settings of KDtree.

Specified by:

getOptions in interface OptionHandler

Overrides:

getOptions in class NearestNeighbourSearch

Returns:

an array of strings suitable for passing to setOptions

kNearestNeighbours

public Instances kNearestNeighbours(Instance target,
                           int k)
                             throws Exception

Returns k-NNs of a given target instance, from among the previously supplied training instances (supplied through setInstances method) P.S.: May return more than k-NNs if more one instances have the same distance to the target as the kth NN.

Specified by:

kNearestNeighbours in class NearestNeighbourSearch

Parameters:

target - The instance for which k-NNs are required.

k - The number of k-NNs to find.

Returns:

The k-NN instances of the given target instance.

Throws:

Exception - If there is some problem find the k-NNs.

nearestNeighbour

public Instance nearestNeighbour(Instance target)
                          throws Exception

Returns the NN instance of a given target instance, from among the previously supplied training instances.

Specified by:

nearestNeighbour in class NearestNeighbourSearch

Parameters:

target - The instance for which NN is required.

Returns:

The NN instance of the target instance.

Throws:

Exception - If there is some problem finding the nearest neighbour.

getDistances

public double[] getDistances()
                      throws Exception

Returns the distances of the (k)-NN(s) found earlier by kNearestNeighbours()/nearestNeighbour().

Specified by:

getDistances in class NearestNeighbourSearch

Returns:

The distances (in the same order) of the k-NNs.

Throws:

Exception - If the tree hasn't been built (by calling setInstances()), or none of kNearestNeighbours() or nearestNeighbour() has been called before.

setInstances

public void setInstances(Instances instances)
                  throws Exception

Builds the Cover Tree on the given set of instances.

Overrides:

setInstances in class NearestNeighbourSearch

Parameters:

instances - The insts on which the Cover Tree is to be built.

Throws:

Exception - If some error occurs while building the Cover Tree

update

public void update(Instance ins)
            throws Exception

Adds an instance to the cover tree. P.S.: The current version doesn't allow addition of instances after batch construction.

Specified by:

update in class NearestNeighbourSearch

Parameters:

ins - The instance to add.

Throws:

Exception - Alway throws this, as current implementation doesn't allow addition of instances after building.

addInstanceInfo

public void addInstanceInfo(Instance ins)

Adds the given instance info. This implementation updates only the range datastructures of the EuclideanDistance. Nothing is required to be updated in the built Cover Tree.

Overrides:

addInstanceInfo in class NearestNeighbourSearch

Parameters:

ins - The instance to add the information of. Usually this is the test instance supplied to update the range of attributes in the distance function.

setDistanceFunction

public void setDistanceFunction(DistanceFunction df)
                         throws Exception

Sets the distance function to use for nearest neighbour search. Currently only EuclideanDistance is supported.

Overrides:

setDistanceFunction in class NearestNeighbourSearch

Parameters:

df - the distance function to use

Throws:

Exception - if not EuclideanDistance

baseTipText

public String baseTipText()

Returns the tip text for this property.

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

getBase

public double getBase()

Returns the base in use for expansion constant.

Returns:

base currently in use.

setBase

public void setBase(double b)

Sets the base to use for expansion constant. The 2 in 2^i in the paper.

Parameters:

b - the new base;

measureTreeSize

public double measureTreeSize()

Returns the size of the tree. (number of internal nodes + number of leaves)

Returns:

the size of the tree

measureNumLeaves

public double measureNumLeaves()

Returns the number of leaves.

Returns:

the number of leaves

measureMaxDepth

public double measureMaxDepth()

Returns the depth of the tree.

Returns:

the number of rules

enumerateMeasures

public Enumeration<String> enumerateMeasures()

Returns an enumeration of the additional measure names.

Specified by:

enumerateMeasures in interface AdditionalMeasureProducer

Overrides:

enumerateMeasures in class NearestNeighbourSearch

Returns:

an enumeration of the measure names

getMeasure

public double getMeasure(String additionalMeasureName)

Returns the value of the named measure.

Specified by:

getMeasure in interface AdditionalMeasureProducer

Overrides:

getMeasure in class NearestNeighbourSearch

Parameters:

additionalMeasureName - the name of the measure to query for its value

Returns:

the value of the named measure

Throws:

IllegalArgumentException - if the named measure is not supported

getRevision

public String getRevision()

Returns the revision string.

Specified by:

getRevision in interface RevisionHandler

Returns:

the revision

main

public static void main(String[] args)

Method for testing the class from command line.

Parameters:

args - The supplied command line arguments.