Build an NN-Descent index — rs_nndescent_build • annsearchR

Use NNDescentIndex instead.

Usage

rs_nndescent_build(
  data,
  metric,
  k_graph,
  delta,
  diversify_prob,
  max_iter,
  max_candidates,
  n_trees,
  seed,
  precision,
  verbose
)

Arguments

data: Numeric matrix. Samples x features.
metric: String. One of c("euclidean", "cosine", "manhattan").
k_graph: Integer. Neighbours per node in the graph.
delta: Numeric. Convergence threshold.
diversify_prob: Numeric. Edge pruning probability after descent.
max_iter: Integer or NULL. Iteration cap.
max_candidates: Integer or NULL. Candidates sampled per local join.
n_trees: Integer or NULL. Random projection trees for the seed graph.
seed: Integer. Random seed.
precision: String. "float" or "double".
verbose: Boolean. Print progress.

Value

External pointer to the index.