Package org.ddogleg.nn.alg
package org.ddogleg.nn.alg

ClassDescriptionSelects which axis the data should be split along when given a list of variances.Selects the axis with the largest variance to split.Randomly selects the larger variances.AxisSplitter<P>Selects which dimension the set of points should be split by, which point is used to split the lists, and splits the lists into two sets.Splits the points in KD Tree node by selecting the axis with the largest variance.Exhaustively finds the nearestneighbor to a ndimensional point by considering every possibility.KD Tree is short for kdimensional tree and is a binary tree data structure used for quickly finding the nearestneighbor of a kdimensional point in a set.Data type for each node in the binary tree.Creates a new
KDTree
from a list of points and (optional) associated data.Computes the distance between two points.KdTreeMemory<P>Memory management for recycling KdTree data structures.Storage for the results of a KD Tree search.Interface for searching a single tree for the nearestneighborInterface for searching a single tree for the N nearestneighbors.Vantage point tree implementation for nearest neighbor search.