[pymvpa] Maximal Vote Issue

[Andrei Rusu]

Hello Everyone,

I have a question about MaximalVote. I'm getting an error on:

voting=MaximalVote(enable_ca=['estimates'])   


TypeError: __init__() got an unexpected keyword argument 'enable_ca'


The documentation page : http://www.pymvpa.org/generated/mvpa.clfs.meta.MaximalVote.html#mvpa.clfs.meta.MaximalVote 
shows "enable_ca" as a valid argument.

I am using python-pymvpa-snapshot from neuro-debian in ubuntu 10.10, 64bit.

I am using this object in the following context:
# inner_part is a custom partitioner which provides random subsets of the training set 
voting = MaximalVote() 
                                        # voting=MaximalVote(enable_ca=['estimates'])    # desired but produces error
      comb_clf = SplitClassifier(LinearCSVMC(C=1), 
partitioner=inner_part, 
splitter=splitter, 
combiner=voting)
 spartitions = partitions[:, indices]
  tm = TransferMeasure(comb_clf, splitter, 
postproc=BinaryFxNode(mean_mismatch_error, space='targets'),  
enable_ca=['stats','raw_results'])
 tm(spartitions)

I would like to see the "estimates: Estimates keep counts across classifiers for each label/sample"

As you might have guessed, this intends to be example-wise bagging.


Any suggestions on how to circumvent this issue or make sure the voting procedure operates as expected?


Many thanks!
Andrei
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