Class KMeansInpiredMethod
java.lang.Object
weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter
weka.core.neighboursearch.kdtrees.KMeansInpiredMethod
- All Implemented Interfaces:
Serializable,OptionHandler,RevisionHandler,TechnicalInformationHandler
The class that splits a node into two such that the
overall sum of squared distances of points to their centres on both sides of
the (axis-parallel) splitting plane is minimum.
For more information see also:
Ashraf Masood Kibriya (2007). Fast Algorithms for Nearest Neighbour Search. Hamilton, New Zealand. BibTeX:
For more information see also:
Ashraf Masood Kibriya (2007). Fast Algorithms for Nearest Neighbour Search. Hamilton, New Zealand. BibTeX:
@mastersthesis{Kibriya2007,
address = {Hamilton, New Zealand},
author = {Ashraf Masood Kibriya},
school = {Department of Computer Science, School of Computing and Mathematical Sciences, University of Waikato},
title = {Fast Algorithms for Nearest Neighbour Search},
year = {2007}
}
- Version:
- $Revision: 10203 $
- Author:
- Ashraf M. Kibriya (amk14[at-the-rate]cs[dot]waikato[dot]ac[dot]nz)
- See Also:
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Field Summary
Fields inherited from class weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter
MAX, MIN, WIDTH -
Constructor Summary
Constructors -
Method Summary
Modifier and TypeMethodDescriptionReturns the revision string.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.Returns a string describing this nearest neighbour search algorithm.voidsplitNode(KDTreeNode node, int numNodesCreated, double[][] nodeRanges, double[][] universe) Splits a node into two such that the overall sum of squared distances of points to their centres on both sides of the (axis-parallel) splitting plane is minimum.Methods inherited from class weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter
getOptions, listOptions, setEuclideanDistanceFunction, setInstanceList, setInstances, setNodeWidthNormalization, setOptions
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Constructor Details
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KMeansInpiredMethod
public KMeansInpiredMethod()
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Method Details
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globalInfo
Returns a string describing this nearest neighbour search algorithm.- Returns:
- a description of the algorithm for displaying in the explorer/experimenter gui
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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:
getTechnicalInformationin interfaceTechnicalInformationHandler- Returns:
- the technical information about this class
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splitNode
public void splitNode(KDTreeNode node, int numNodesCreated, double[][] nodeRanges, double[][] universe) throws Exception Splits a node into two such that the overall sum of squared distances of points to their centres on both sides of the (axis-parallel) splitting plane is minimum. The two nodes created after the whole splitting are correctly initialised. And, node.left and node.right are set appropriately.- Specified by:
splitNodein classKDTreeNodeSplitter- 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:
Exception- If there is some problem in splitting the given node.
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getRevision
Returns the revision string.- Specified by:
getRevisionin interfaceRevisionHandler- Overrides:
getRevisionin classKDTreeNodeSplitter- Returns:
- the revision
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