| umap {umap} | R Documentation | 
Computes a manifold approximation and projection
Description
Computes a manifold approximation and projection
Usage
umap(
  d,
  config = umap.defaults,
  method = c("naive", "umap-learn"),
  preserve.seed = TRUE,
  ...
)
Arguments
d | 
 matrix, input data  | 
config | 
 object of class umap.config  | 
method | 
 character, implementation. Available methods are 'naive' (an implementation written in pure R) and 'umap-learn' (requires python package 'umap-learn')  | 
preserve.seed | 
 logical, leave TRUE to insulate external code from randomness within the umap algorithms; set FALSE to allow randomness used in umap algorithms to alter the external random-number generator  | 
... | 
 list of settings; values overwrite defaults from config; see documentation of umap.default for details about available settings  | 
Value
object of class umap, containing at least a component with an embedding and a component with configuration settings
Examples
# embedd iris dataset using default settings
iris.umap = umap(iris[,1:4])
# display object summary
iris.umap
# display embedding coordinates
head(iris.umap$layout)
[Package umap version 0.2.10.0 Index]