weka.core.neighboursearch
Class BallTree

java.lang.Object
  extended by weka.core.neighboursearch.NearestNeighbourSearch
      extended by weka.core.neighboursearch.BallTree
All Implemented Interfaces:
java.io.Serializable, AdditionalMeasureProducer, OptionHandler, 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)

Version:
$Revision: 1.1 $
Author:
Ashraf M. Kibriya (amk14[at-the-rate]cs[dot]waikato[dot]ac[dot]nz)
See Also:
Serialized Form

Constructor Summary
BallTree()
          Creates a new instance of BallTree.
BallTree(Instances insts)
          Creates a new instance of BallTree.
 
Method Summary
 void addInstanceInfo(Instance ins)
          Adds the given instance's info.
 java.lang.String ballTreeConstructorTipText()
          Returns the tip text for this property.
 java.util.Enumeration 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.
 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 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.
 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, quickSort, setDistanceFunction
 
Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 

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

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.

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 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 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