The functions documented here allow to compare the fits computed in different NMF runs. The fits do not need to be from the same algorithm, nor have the same dimension.
S4 (NMFfit) `compare`(object, ...) S4 (list) `compare`(object, ...) S4 (NMFList) `summary`(object, sort.by = NULL, select = NULL, ...) S4 (NMFList,missing) `plot`(x, y, skip = -1, ...) S4 (NMF.rank) `consensusmap`(object, ...) S4 (list) `consensusmap`(object, layout, Rowv = FALSE, main = names(object), ...)
compare
to summary,NMFList
or to the summary
method of each fit.data.frame
. The
column are given by their names (partially matched). The column names are
the names of the summary measures returned by the summary
methods of
the corresponding NMF results.data.frame
is sorted. The sorting direction
(increasing or decreasing) is computed internally depending on the chosen
criteria (e.g. decreasing for the cophenetic coefficient, increasing for the
residuals).NMFList
object that contains fits from separate NMF runs.layout
from the package graphics
.skip=1L
(default) only the initial residual -- that is computed before any iteration, is
skipped, if present in the track (it associated with iteration 0).The methods compare
enables to compare multiple NMF fits either
passed as arguments or as a list of fits.
These methods eventually call the method summary,NMFList
, so that
all its arguments can be passed named in ...
.
signature(object = "NMFfit")
: Compare multiple NMF fits passed as arguments.
signature(object = "list")
: Compares multiple NMF fits passed as a standard list.
signature(object = "NMF.rank")
: Draw a single plot with a heatmap of the consensus matrix obtained for each value of the rank,
in the range tested with nmfEstimateRank
.
signature(object = "list")
: Draw a single plot with a heatmap of the consensus matrix of each element in the list object
.
signature(x = "NMFList", y = "missing")
: plot
plot on a single graph the residuals tracks for each fit in x
.
See function nmf
for details on how to enable the tracking of residuals.
signature(object = "NMFList")
: summary,NMFList
computes summary measures for each NMF result in the list
and return them in rows in a data.frame
.
By default all the measures are included in the result, and NA
values
are used where no data is available or the measure does not apply to the
result object (e.g. the dispersion for single' NMF runs is not meaningful).
This method is very useful to compare and evaluate the performance of
different algorithms.