knn {destiny}R Documentation

kNN search

Description

k nearest neighbor search with custom distance function.

Usage

find_knn(data, k, ..., query = NULL, distance = c("euclidean", "cosine",
  "rankcor"), sym = TRUE)

Arguments

data

Data matrix

k

Number of nearest neighbors

...

All parameters after this have to be specified by name

query

Query matrix. In knn and knn_asym, query and data are identical

distance

Distance metric to use. Allowed measures: Euclidean distance (default), cosine distance (1-corr(c_1, c_2)) or rank correlation distance (1-corr(rank(c_1), rank(c_2)))

sym

Return a symmetric matrix (as long as query is NULL)?

Value

A dgCMatrix if sym == TRUE, else a dsCMatrix (nrow(query) \times nrow(data)).


[Package destiny version 2.10.2 Index]