[BioC] Applying classifiers derived from CMA
Mike Dewar
mike.dewar at columbia.edu
Tue May 18 20:00:00 CEST 2010
Hi,
I've trained up a classifier using the (so-far wonderful) CMA package. It validated well, and gives me predictions that agree well with my labels. I'd now like to use the classifier on a held-out data set, but for the life of me I can't figure out how to apply a classifier to a new example. Does anyone have any ideas?
For example, having loaded my `exprset` and generated a `learning_set` using CMA's GenerateLearningsets(), I can run the classification() function as follows:
out = classification(
X = t(exprs(exprset)),
y = pData(exprset)$labels,
learningsets = learning_set,
classifier = rfCMA
)
the object `out` gives me loads of information about how well it did and so on, but I can't seem to use "out" in order to classifiy a new set. An alternative approach would be to run something like classification() whereby I give it an X_test variable or something, but this doesn't seem to be available.
Any help would be greatly appreciated : I'm sure I'm missing something basic!
Cheers,
Mike Dewar
- - -
Dr Michael Dewar
Postdoctoral Research Scientist
Applied Mathematics
Columbia University
http://www.columbia.edu/~md2954/
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