CoverTree

java.lang.Object
- weka.core.neighboursearch.NearestNeighbourSearch
- - weka.core.neighboursearch.CoverTree

All Implemented Interfaces:

java.io.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: 1.4 $

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.

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.

Constructors
Constructor and Description
`CoverTree()` default constructor.

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`void`	`addInstanceInfo(Instance ins)` Adds the given instance info.
`java.lang.String`	`baseTipText()` Returns the tip text for this property.
`java.util.Enumeration`	`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(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-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.
`java.util.Enumeration`	`listOptions()` Returns an enumeration describing the available options.
`static void`	`main(java.lang.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(java.lang.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 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
  - 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:
```
 -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:
    
    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
  - kNearestNeighbours
```
public Instances kNearestNeighbours(Instance target,
                                    int k)
                             throws java.lang.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:
    
    java.lang.Exception - If there is some problem find the k-NNs.
  - nearestNeighbour
```
public Instance nearestNeighbour(Instance target)
                          throws java.lang.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:
    
    java.lang.Exception - If there is some problem finding the nearest neighbour.
  - getDistances
```
public double[] getDistances()
                      throws java.lang.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:
    
    java.lang.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 java.lang.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:
    
    java.lang.Exception - If some error occurs while building the Cover Tree
  - update
```
public void update(Instance ins)
            throws java.lang.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:
    
    java.lang.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 java.lang.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:
    
    java.lang.Exception - if not EuclideanDistance
  - baseTipText
```
public java.lang.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 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
  - getRevision
```
public java.lang.String getRevision()
```
    Returns the revision string.
    
    Specified by:
    
    getRevision in interface RevisionHandler
    
    Returns:
    
    the revision
  - main
```
public static void main(java.lang.String[] args)
```
    Method for testing the class from command line.
    
    Parameters:
    
    args - The supplied command line arguments.

Class CoverTree

Nested Class Summary

Constructor Summary

Method Summary

Methods inherited from class weka.core.neighboursearch.NearestNeighbourSearch

Methods inherited from class java.lang.Object

Constructor Detail

CoverTree

Method Detail

globalInfo

getTechnicalInformation

listOptions

setOptions

getOptions

kNearestNeighbours

nearestNeighbour

getDistances

setInstances

update

addInstanceInfo

setDistanceFunction

baseTipText

getBase

setBase

measureTreeSize

measureNumLeaves

measureMaxDepth

enumerateMeasures

getMeasure

getRevision

main