KDTreePartitioner: k-d tree partitioner

In cleanzr/dblinkR: R interface for dblink

Description

Partitions the space of entities into blocks using a k-d tree. Each node of the tree is associated with a splitting rule that divides the input space into two parts, based on the value of one of the attributes. The tree is fitted using the observed records, and the splits are chosen to yield a balanced tree. The depth of the tree and the attributes used for splitting at each level are user-specified parameters.

Usage

KDTreePartitioner(numLevels, attributes)

Arguments

numLevels	The depth/number of levels of the tree. The partitions are the leaves of the tree, hence the number of partitions is given by 2^numLevels.
attributes	The attributes used for splitting at each level of the tree are taken by cycling through this vector. For example, if attributes = c("A", "B"), the split at the 0-th level is based on attribute "A", the split at the 1-st level is based on attribute "B", the split at the 2-nd level is based on attribute "A", etc.

Examples

# Specify a partitioner for RLdata10000
partitioner <- KDTreePartitioner(numLevels = 2, attributes = c("fname_c1", "by"))

cleanzr/dblinkR documentation built on June 13, 2021, 4:17 a.m.