weka.core.neighboursearch

Class BallTree

java.lang.Object

weka.core.neighboursearch.NearestNeighbourSearch

weka.core.neighboursearch.BallTree

All Implemented Interfaces:

java.io.Serializable, AdditionalMeasureProducer, OptionHandler, RevisionHandler, TechnicalInformationHandler

public class BallTree
extends NearestNeighbourSearch
implements TechnicalInformationHandler

Class implementing the BallTree/Metric Tree algorithm for nearest neighbour search.
The connection to dataset is only a reference. For the tree structure the indexes are stored in an array.
See the implementing classes of different construction methods of the trees for details on its construction.

For more information see also:

Stephen M. Omohundro (1989). Five Balltree Construction Algorithms.

Jeffrey K. Uhlmann (1991). Satisfying general proximity/similarity queries with metric trees. Information Processing Letters. 40(4):175-179.

BibTeX:

 @techreport{Omohundro1989,
    author = {Stephen M. Omohundro},
    institution = {International Computer Science Institute},
    month = {December},
    number = {TR-89-063},
    title = {Five Balltree Construction Algorithms},
    year = {1989}
 }
 
 @article{Uhlmann1991,
    author = {Jeffrey K. Uhlmann},
    journal = {Information Processing Letters},
    month = {November},
    number = {4},
    pages = {175-179},
    title = {Satisfying general proximity/similarity queries with metric trees},
    volume = {40},
    year = {1991}
 }
 

Valid options are:

 -C <classname and options>
  The construction method to employ. Either TopDown or BottomUp
  (default: weka.core.TopDownConstructor)

See Also:

Serialized Form

Nested Class Summary

Nested classes/interfaces inherited from class weka.core.neighboursearch.NearestNeighbourSearch

NearestNeighbourSearch.MyHeap, NearestNeighbourSearch.MyHeapElement, NearestNeighbourSearch.NeighborList, NearestNeighbourSearch.NeighborNode

Field Summary

Fields

Modifier and Type	Field and Description
protected double[]	m_Distances Array holding the distances of the nearest neighbours.
protected int[]	m_InstList The instances indices sorted inorder of appearence in the tree from left most leaf node to the right most leaf node.
protected int	m_MaxInstancesInLeaf The maximum number of instances in a leaf.
protected BallNode	m_Root The root node of the BallTree.
protected BallTreeConstructor	m_TreeConstructor The constructor method to use to build the tree.
protected TreePerformanceStats	m_TreeStats Tree Stats variables.

Fields inherited from class weka.core.neighboursearch.NearestNeighbourSearch

m_DistanceFunction, m_Instances, m_kNN, m_MeasurePerformance, m_Stats

Constructor Summary

Constructors

Constructor and Description
BallTree() Creates a new instance of BallTree.
BallTree(Instances insts) Creates a new instance of BallTree.

Method Summary

Modifier and Type	Method and Description
void	addInstanceInfo(Instance ins) Adds the given instance's info.
java.lang.String	ballTreeConstructorTipText() Returns the tip text for this property.
protected void	buildTree() Builds the BallTree on the supplied set of instances/points (supplied with setInstances(Instances) method and referenced by the m_Instances field).
java.util.Enumeration<java.lang.String>	enumerateMeasures() Returns an enumeration of the additional measure names.
BallTreeConstructor	getBallTreeConstructor() Returns the BallTreeConstructor currently in use.
double[]	getDistances() Returns the distances of the k nearest neighbours.
double	getMeasure(java.lang.String additionalMeasureName) Returns the value of the named measure.
java.lang.String[]	getOptions() Gets the current settings of KDtree.
java.lang.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.
java.lang.String	globalInfo() Returns a string describing this nearest neighbour search algorithm.
Instances	kNearestNeighbours(Instance target, int k) Returns k nearest instances in the current neighbourhood to the supplied instance.
java.util.Enumeration<Option>	listOptions() Returns an enumeration describing the available options.
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 nearest instance in the current neighbourhood to the supplied instance.
protected void	nearestNeighbours(NearestNeighbourSearch.MyHeap heap, BallNode node, Instance target, int k) Does NN search according to Moore's method.
void	setBallTreeConstructor(BallTreeConstructor constructor) Sets the BallTreeConstructor for building the BallTree (default TopDownConstructor).
void	setInstances(Instances insts) Builds the BallTree based on the given set of instances.
void	setMeasurePerformance(boolean measurePerformance) Sets whether to calculate the performance statistics or not.
void	setOptions(java.lang.String[] options) Parses a given list of options
void	update(Instance ins) Adds one instance to the BallTree.

Methods inherited from class weka.core.neighboursearch.NearestNeighbourSearch

combSort11, distanceFunctionTipText, getDistanceFunction, getInstances, getMeasurePerformance, getPerformanceStats, measurePerformanceTipText, partition, quickSort, setDistanceFunction

Methods inherited from class java.lang.Object

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

Field Detail

m_InstList

protected int[] m_InstList

The instances indices sorted inorder of appearence in the tree from left most leaf node to the right most leaf node.

m_MaxInstancesInLeaf

protected int m_MaxInstancesInLeaf

The maximum number of instances in a leaf. A node is made into a leaf if the number of instances in it become less than or equal to this value.

m_TreeStats

protected TreePerformanceStats m_TreeStats

Tree Stats variables.

m_Root

protected BallNode m_Root

The root node of the BallTree.

m_TreeConstructor

protected BallTreeConstructor m_TreeConstructor

The constructor method to use to build the tree.

m_Distances

protected double[] m_Distances

Array holding the distances of the nearest neighbours. It is filled up both by nearestNeighbour() and kNearestNeighbours().

Constructor Detail

BallTree

public BallTree()

Creates a new instance of BallTree.

BallTree

public BallTree(Instances insts)

Creates a new instance of BallTree. It also builds the tree on supplied set of Instances.

Parameters:

insts - The instances/points on which the BallTree should be built on.

Method Detail

globalInfo

public java.lang.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

buildTree

protected void buildTree()
                  throws java.lang.Exception

Builds the BallTree on the supplied set of instances/points (supplied with setInstances(Instances) method and referenced by the m_Instances field). This method should not be called by outside classes. They should only use setInstances(Instances) method.

Throws:

java.lang.Exception - If no instances are supplied (m_Instances is null), or if some other error in the supplied BallTreeConstructor occurs while building the tree.

kNearestNeighbours

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

Returns k nearest instances in the current neighbourhood to the supplied instance. >k instances can be returned if there is more than one instance at the kth boundary (i.e. if there are more than 1 instance with the same distance as the kth nearest neighbour).

Specified by:

kNearestNeighbours in class NearestNeighbourSearch

Parameters:

target - The instance to find the k nearest neighbours for.

k - The number of nearest neighbours to find.

Returns:

The k nearest neighbours of the given target instance (>k nearest neighbours, if there are more instances that have same distance as the kth nearest neighbour).

Throws:

java.lang.Exception - If the neighbours could not be found.

nearestNeighbours

protected void nearestNeighbours(NearestNeighbourSearch.MyHeap heap,
                                 BallNode node,
                                 Instance target,
                                 int k)
                          throws java.lang.Exception

Does NN search according to Moore's method. Should not be used by outside classes. They should instead use kNearestNeighbours(Instance, int). P.S.: The distance returned are squared. Need to post process the distances.

Parameters:

heap - MyHeap object to store/update NNs found during the search.

node - The BallNode to do the NN search on.

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

k - The number of NNs to find.

Throws:

java.lang.Exception - If the structure of the BallTree is not correct, or if there is some problem putting NNs in the heap.

nearestNeighbour

public Instance nearestNeighbour(Instance target)
                          throws java.lang.Exception

Returns the nearest instance in the current neighbourhood to the supplied instance.

Specified by:

nearestNeighbour in class NearestNeighbourSearch

Parameters:

target - The instance to find the nearest neighbour for.

Returns:

The nearest neighbour of the given target instance.

Throws:

java.lang.Exception - if the nearest neighbour could not be found.

getDistances

public double[] getDistances()
                      throws java.lang.Exception

Returns the distances of the k nearest neighbours. The kNearestNeighbours or nearestNeighbour must always be called before calling this function. If this function is called before calling either the kNearestNeighbours or the nearestNeighbour, then it throws an exception. If, however, any one of the two functions is called at any point in the past, then no exception is thrown and the distances of NN(s) from the training set for the last supplied target instance (to either one of the nearestNeighbour functions) is/are returned.

Specified by:

getDistances in class NearestNeighbourSearch

Returns:

array containing the distances of the nearestNeighbours. The length and ordering of the array is the same as that of the instances returned by nearestNeighbour functions.

Throws:

java.lang.Exception - if called before calling kNearestNeighbours or nearestNeighbours.

update

public void update(Instance ins)
            throws java.lang.Exception

Adds one instance to the BallTree. This involves creating/updating the structure to reflect the newly added training instance

Specified by:

update in class NearestNeighbourSearch

Parameters:

ins - The instance to be added. Usually the newly added instance in the training set.

Throws:

java.lang.Exception - If the instance cannot be added to the tree.

addInstanceInfo

public void addInstanceInfo(Instance ins)

Adds the given instance's info. This implementation updates the attributes' range datastructures of EuclideanDistance class.

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.

setInstances

public void setInstances(Instances insts)
                  throws java.lang.Exception

Builds the BallTree based on the given set of instances.

Overrides:

setInstances in class NearestNeighbourSearch

Parameters:

insts - The insts for which the BallTree is to be built.

Throws:

java.lang.Exception - If some error occurs while building the BallTree

ballTreeConstructorTipText

public java.lang.String ballTreeConstructorTipText()

Returns the tip text for this property.

Returns:

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

getBallTreeConstructor

public BallTreeConstructor getBallTreeConstructor()

Returns the BallTreeConstructor currently in use.

Returns:

The BallTreeConstructor currently in use.

setBallTreeConstructor

public void setBallTreeConstructor(BallTreeConstructor constructor)

Sets the BallTreeConstructor for building the BallTree (default TopDownConstructor).

Parameters:

constructor - The new BallTreeConstructor.

measureTreeSize

public double measureTreeSize()

Returns the size of the tree.

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 java.util.Enumeration<java.lang.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(java.lang.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:

java.lang.IllegalArgumentException - if the named measure is not supported.

setMeasurePerformance

public void setMeasurePerformance(boolean measurePerformance)

Sets whether to calculate the performance statistics or not.

Overrides:

setMeasurePerformance in class NearestNeighbourSearch

Parameters:

measurePerformance - This should be true if performance statistics are to be calculated.

listOptions

public java.util.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(java.lang.String[] options)
                throws java.lang.Exception

Parses a given list of options. Valid options are:

 -C <classname and options>
  The construction method to employ. Either TopDown or BottomUp
  (default: weka.core.TopDownConstructor)

Specified by:

setOptions in interface OptionHandler

Overrides:

setOptions in class NearestNeighbourSearch

Parameters:

options - the list of options as an array of strings

Throws:

java.lang.Exception - if an option is not supported

getOptions

public java.lang.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

getRevision

public java.lang.String getRevision()

Returns the revision string.

Specified by:

getRevision in interface RevisionHandler

Returns:

the revision