Package moa.clusterers.kmeanspm
Class ClusteringTreeHeadNode
- java.lang.Object
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- moa.AbstractMOAObject
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- moa.clusterers.kmeanspm.ClusteringTreeNode
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- moa.clusterers.kmeanspm.ClusteringTreeHeadNode
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- All Implemented Interfaces:
Serializable
,MOAObject
public class ClusteringTreeHeadNode extends ClusteringTreeNode
Provides a ClusteringTreeNode with an extended nearest neighbor search in the root. Citation: Hendrik Fichtenberger, Marc Gillé, Melanie Schmidt, Chris Schwiegelshohn, Christian Sohler: BICO: BIRCH Meets Coresets for k-Means Clustering. ESA 2013: 481-492 (2013) http://ls2-www.cs.tu-dortmund.de/bico/- See Also:
- Serialized Form
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Constructor Summary
Constructors Constructor Description ClusteringTreeHeadNode(double[] center, ClusteringFeature cf, int dimension, int numProjections, int hashSize, Random random)
Creates a ClusteringTreeNode with an extended nearest neighbor search in the root.
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description boolean
addChild(ClusteringTreeNode e)
Adds a child node.void
clearChildren()
Removes all children nodes.ClusteringTreeNode
nearestChild(double[] pointA)
Searches for the nearest child node by comparing each representation.-
Methods inherited from class moa.clusterers.kmeanspm.ClusteringTreeNode
addToClustering, addToClusteringCenters, count, getCenter, getChildren, getClusteringFeature, getDescription, getThreshold, hasNoChildren, printClusteringCenters, setCenter, setThreshold
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Methods inherited from class moa.AbstractMOAObject
copy, copy, measureByteSize, measureByteSize, toString
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Constructor Detail
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ClusteringTreeHeadNode
public ClusteringTreeHeadNode(double[] center, ClusteringFeature cf, int dimension, int numProjections, int hashSize, Random random)
Creates a ClusteringTreeNode with an extended nearest neighbor search in the root.- Parameters:
dimension
- the number of dimensions of the pointsnumProjections
- the number of projections to use for the nearest neighbor searchhashSize
- size of the hash function (must be smaller than 31)random
- instance to generate a stream of pseudorandom numbers
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Method Detail
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nearestChild
public ClusteringTreeNode nearestChild(double[] pointA)
Description copied from class:ClusteringTreeNode
Searches for the nearest child node by comparing each representation.- Overrides:
nearestChild
in classClusteringTreeNode
- Parameters:
pointA
- to find the nearest child for- Returns:
- the child node which is the nearest
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addChild
public boolean addChild(ClusteringTreeNode e)
Description copied from class:ClusteringTreeNode
Adds a child node.- Overrides:
addChild
in classClusteringTreeNode
- Parameters:
e
- the child node to add- Returns:
true
- See Also:
List.add(java.lang.Object)
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clearChildren
public void clearChildren()
Description copied from class:ClusteringTreeNode
Removes all children nodes.- Overrides:
clearChildren
in classClusteringTreeNode
- See Also:
List.clear()
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