Uses of Class
moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNode

Packages that use KDTreeNode

Package	Description
moa.classifiers.lazy.neighboursearch
moa.classifiers.lazy.neighboursearch.kdtrees

Uses of KDTreeNode in moa.classifiers.lazy.neighboursearch

Fields in moa.classifiers.lazy.neighboursearch declared as KDTreeNode

Modifier and Type	Field and Description
protected KDTreeNode	KDTree.m_Root The root node of the tree.

Methods in moa.classifiers.lazy.neighboursearch with parameters of type KDTreeNode

Modifier and Type	Method and Description
protected void	KDTree.addInstanceToTree(weka.core.Instance inst, KDTreeNode node) Recursively adds an instance to the tree starting from the supplied KDTreeNode.
protected void	KDTree.afterAddInstance(KDTreeNode node) Corrects the start and end indices of a KDTreeNode after an instance is added to the tree.
void	KDTree.assignSubToCenters(KDTreeNode node, weka.core.Instances centers, int[] centList, int[] assignments) Assigns instances of this node to center.
protected boolean	KDTree.candidateIsFullOwner(KDTreeNode node, weka.core.Instance candidate, weka.core.Instance competitor) Returns true if candidate is a full owner in respect to a competitor.
protected boolean	KDTree.clipToInsideHrect(KDTreeNode node, weka.core.Instance x) Finds the closest point in the hyper rectangle to a given point.
protected void	KDTree.determineAssignments(KDTreeNode node, weka.core.Instances centers, int[] candidates, int[] assignments, double pc) Assigns instances to the current centers called candidates.
protected double	KDTree.distanceToHrect(KDTreeNode node, weka.core.Instance x) Returns the distance between a point and an hyperrectangle.
protected void	KDTree.findNearestNeighbours(weka.core.Instance target, KDTreeNode node, int k, NearestNeighbourSearch.MyHeap heap, double distanceToParents) Returns (in the supplied heap object) the k nearest neighbours of the given instance starting from the give tree node.
protected int[]	KDTree.refineOwners(KDTreeNode node, weka.core.Instances centers, int[] candidates) Refines the ownerlist.
protected void	KDTree.splitNodes(KDTreeNode node, double[][] universe, int depth) Recursively splits nodes of a tree starting from the supplied node.

Uses of KDTreeNode in moa.classifiers.lazy.neighboursearch.kdtrees

Fields in moa.classifiers.lazy.neighboursearch.kdtrees declared as KDTreeNode

Modifier and Type	Field and Description
KDTreeNode	KDTreeNode.m_Left left subtree; contains instances with smaller or equal to split value.
KDTreeNode	KDTreeNode.m_Right right subtree; contains instances with larger than split value.

Methods in moa.classifiers.lazy.neighboursearch.kdtrees with parameters of type KDTreeNode

Modifier and Type	Method and Description
void	KMeansInpiredMethod.splitNode(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.
void	MidPointOfWidestDimension.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.
void	MedianOfWidestDimension.splitNode(KDTreeNode node, int numNodesCreated, double[][] nodeRanges, double[][] universe) Splits a node into two based on the median value of the dimension in which the points have the widest spread.
void	SlidingMidPointOfWidestSide.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 node's rectangle is widest.
abstract void	KDTreeNodeSplitter.splitNode(KDTreeNode node, int numNodesCreated, double[][] nodeRanges, double[][] universe) Splits a node into two.