control_kd: Controls for the k-d tree algorithm

In blocking: Various Blocking Methods for Entity Resolution

Controls for the k-d tree algorithm

Description

Controls for KD algorithm used in the package (see knn for details).

Usage

control_kd(
  algorithm = "dual_tree",
  epsilon = 0,
  leaf_size = 20,
  random_basis = FALSE,
  rho = 0.7,
  tau = 0,
  tree_type = "kd",
  ...
)

Arguments

algorithm	Type of neighbor search: 'naive', 'single_tree', 'dual_tree', 'greedy'.
epsilon	If specified, will do approximate nearest neighbor search with given relative error.
leaf_size	Leaf size for tree building (used for kd-trees, vp trees, random projection trees, UB trees, R trees, R* trees, X trees, Hilbert R trees, R+ trees, R++ trees, spill trees, and octrees).
random_basis	Before tree-building, project the data onto a random orthogonal basis.
rho	Balance threshold (only valid for spill trees).
tau	Overlapping size (only valid for spill trees).
tree_type	Type of tree to use: 'kd', 'vp', 'rp', 'max-rp', 'ub', 'cover', 'r', 'r-star', 'x', 'ball', 'hilbert-r', 'r-plus', 'r-plus-plus', 'spill', 'oct'.
...	Additional arguments.

Value

Returns a list with parameters.

blocking documentation built on June 18, 2025, 9:16 a.m.