bdm.merge.s2nr | R Documentation |
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.
bdm.merge.s2nr(
data,
bdm,
k = 10,
plot.merge = T,
ret.merge = F,
info = T,
layer = 1,
...
)
data |
Input data (a matrix, a big.matrix or a .csv file name). |
bdm |
A bdm instance as generated by |
k |
The number of desired clusters. The clustering will be recursively merged until reaching this number of clusters (default value is |
plot.merge |
Logical value. If TRUE, the merged clustering is plotted (default value is |
ret.merge |
Logical value. If TRUE, the function returns a copy of the input bdm instance with the merged clustering attached as bdm$merge (default value is |
info |
Logical value. If TRUE, all merging steps are shown (default value is |
layer |
The bdm$ptsne layer to be used (default value is |
... |
If plot.merge is TRUE, you can set the |
See details in bdm.optk.s2nr()
.
None if ret.merge = FALSE
. Else, a copy of the input bdm instance with new element bdm$merge.
bdm.example()
m.labels <- bdm.labels(ex$map)
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