Barplot {CMA} | R Documentation |
This method can be seen as a visual pendant to
toplist
. The plot visualizes
variable importance by a barplot. The height
of the barplots correspond to variable importance.
What variable importance exactly means depends
on the method chosen when calling GeneSelection
,
s. genesel
.
x |
An object of class genesel |
top |
Number of top genes whose variable importance should be displayed. Defaults to 10. |
iter |
Iteration number (learningset ) for which variable
importance should be displayed. |
... |
Further graphical options passed to barplot . |
No return.
Note the following
scheme = "multiclass"
, only one plot will be made.
Otherwise, one plot will be made for each binary scenario
(depending on whether "scheme"
is "one-vs-all"
or "pairwise"
).
"lasso", "elasticnet", "boosting"
the number of nonzero coefficients can be very small, resulting
in bars of height zero if top
has been chosen too
large.
Martin Slawski ms@cs.uni-sb.de
Anne-Laure Boulesteix boulesteix@ibe.med.uni-muenchen.de
Slawski, M. Daumer, M. Boulesteix, A.-L. (2008) CMA - A comprehensive Bioconductor package for supervised classification with high dimensional data. BMC Bioinformatics 9: 439
genesel
, GeneSelection
, toplist