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 2.6.2 Index]