weka.core.neighboursearch.kdtrees

Class MidPointOfWidestDimension

java.lang.Object

weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter

weka.core.neighboursearch.kdtrees.MidPointOfWidestDimension

All Implemented Interfaces:

java.io.Serializable, OptionHandler, RevisionHandler, TechnicalInformationHandler

public class MidPointOfWidestDimension
extends KDTreeNodeSplitter
implements TechnicalInformationHandler

The class that splits a KDTree node based on the midpoint value of a dimension in which the node's points have the widest spread.

For more information see also:

Andrew Moore (1991). A tutorial on kd-trees.

BibTeX:

 @techreport{Moore1991,
    author = {Andrew Moore},
    booktitle = {University of Cambridge Computer Laboratory Technical Report No. 209},
    howpublished = {Extract from PhD Thesis},
    title = {A tutorial on kd-trees},
    year = {1991},
    HTTP = {http://www.autonlab.org/autonweb/14665.html}
 }
 

Version:

$Revision: 1.2 $

Author:

Ashraf M. Kibriya (amk14[at-the-rate]cs[dot]waikato[dot]ac[dot]nz)

See Also:

Serialized Form

Field Summary

Fields inherited from class weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter

MAX, MIN, WIDTH

Constructor Summary

Constructors

Constructor and Description
MidPointOfWidestDimension()

Method Summary

Modifier and Type	Method and Description
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.
void	splitNode(KDTreeNode node, int numNodesCreated, double[][] nodeRanges, double[][] universe) Splits a node into two based on the midpoint value of the dimension in which the points have the widest spread.

Methods inherited from class weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter

getOptions, listOptions, setEuclideanDistanceFunction, setInstanceList, setInstances, setNodeWidthNormalization, setOptions

Methods inherited from class java.lang.Object

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

Constructor Detail

MidPointOfWidestDimension

public MidPointOfWidestDimension()

Method Detail

globalInfo

public java.lang.String globalInfo()

Returns a string describing this nearest neighbour search algorithm.

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

splitNode

public void splitNode(KDTreeNode node,
                      int numNodesCreated,
                      double[][] nodeRanges,
                      double[][] universe)
               throws java.lang.Exception

Splits a node into two based on the midpoint value of the dimension in which the points have the widest spread. After splitting two new nodes are created and correctly initialised. And, node.left and node.right are set appropriately.

Specified by:

splitNode in class KDTreeNodeSplitter

Parameters:

node - The node to split.

numNodesCreated - The number of nodes that so far have been created for the tree, so that the newly created nodes are assigned correct/meaningful node numbers/ids.

nodeRanges - The attributes' range for the points inside the node that is to be split.

universe - The attributes' range for the whole point-space.

Throws:

java.lang.Exception - If there is some problem in splitting the given node.

getRevision

public java.lang.String getRevision()

Returns the revision string.

Specified by:

getRevision in interface RevisionHandler

Overrides:

getRevision in class KDTreeNodeSplitter

Returns:

the revision