Rust-based EVoC clustering — evoc • manifoldsR

Performs EVoC (Embedding Vector Oriented Clustering) on the input data. Combines a UMAP-like node embedding with HDBSCAN-style density-based clustering and multi-layer persistence analysis.

Usage

evoc(
  data,
  knn = NULL,
  n_neighbours = 15L,
  knn_method = c("kmknn", "hnsw", "annoy", "nndescent", "balltree", "ivf", "exhaustive"),
  nn_params = params_nn(),
  evoc_params = params_evoc(),
  return_knn = FALSE,
  seed = 42L,
  .verbose = TRUE
)

Arguments

data: Numerical matrix or data frame. The data to cluster, of shape samples x features. Will be coerced to a matrix.
knn: Optional NearestNeighbours class. If provided, EVoC will skip the kNN graph generation and use this one. Defaults to NULL.
n_neighbours: Integer. Number of nearest neighbours for graph construction. Defaults to 15L.
knn_method: Character. (Approximate) Nearest neighbour method to use. One of "kmknn", "hnsw", "annoy", "nndescent", "balltree", or "exhaustive". Defaults to "kmknn".
nn_params: Named list. Nearest neighbour search parameters, see params_nn().
evoc_params: Named list. EVoC algorithm parameters, see params_evoc().
return_knn: Logical. Whether to return the kNN graph. If knn is provided, it is returned as-is. Defaults to FALSE.
seed: Integer. Random seed for reproducibility. Defaults to 42L.
.verbose: Logical. Controls verbosity. Defaults to TRUE.

Value

An Evoc S3 object (see print.Evoc, best_membership, get_layer).