bdm.merge.s2nr: Merging of clusters based on signal-to-noise-ratio.

View source: R/bdm_merge.R

bdm.merge.s2nrR Documentation

Merging of clusters based on signal-to-noise-ratio.

Description

Performs a recursive merging of clusters based on minimum loss of signal-to-noise-ratio (S2NR) until reaching the desired number of clusters. The S2NR is the explained/unexplained variance ratio measured in the high dimensional space based on the given low dimensional clustering.

Usage

bdm.merge.s2nr(
  data,
  bdm,
  k = 10,
  plot.merge = T,
  ret.merge = F,
  info = T,
  layer = 1,
  ...
)

Arguments

data

Input data (a matrix, a big.matrix or a .csv file name).

bdm

A bdm instance as generated by bdm.init().

k

The number of desired clusters. The clustering will be recursively merged until reaching this number of clusters (default value is k = 10). By setting k < 0 we can specify the number of clusters that we are willing to merge.

plot.merge

Logical value. If TRUE, the merged clustering is plotted (default value is plot.merge = TRUE)

ret.merge

Logical value. If TRUE, the function returns a copy of the input bdm instance with the merged clustering attached as bdm$merge (default value is ret.merge = FALSE)

info

Logical value. If TRUE, all merging steps are shown (default value is info = FALSE).

layer

The bdm$ptsne layer to be used (default value is layer = 1).

...

If plot.merge is TRUE, you can set the bdm.wtt.plot() parameters to control the plot.

Details

See details in bdm.optk.s2nr().

Value

None if ret.merge = FALSE. Else, a copy of the input bdm instance with new element bdm$merge.

Examples


bdm.example()
m.labels <- bdm.labels(ex$map)

jgarriga65/bigMap documentation built on June 10, 2024, 7:05 a.m.