<div>Hi all,</div><div><br></div><div>I am just getting started using PyMVPA so my question is very basic. I am sure the answer must be available already but I just cant seem to find it. Sorry about this, but I hope someone can help me out.</div>
My question is how to get the classification results from the N individual tests using the NFoldSplitter.<div><br></div><div>#Lets say I have a 10 chunks dataset 'ds' and run:</div><div><div> clf = FeatureSelectionClassifier(</div>
<div> LinearCSVMC(),</div><div> SensitivityBasedFeatureSelection(</div><div> OneWayAnova(),</div><div> FractionTailSelector(0.05,mode='select',tail='upper')),</div><div> descr="VA",</div>
<div> enable_states = ['feature_ids'])</div><div><br></div><div> terr = TransferError(clf)</div><div> cvterr = CrossValidatedTransferError(terr,</div><div> NFoldSplitter(cvtype=1),</div>
<div> enable_states=['confusion'])</div><div> </div><div>error = cvterr(ds)</div><div><br></div><div>#If I now do:</div><div> print cvterr.confusion.asstring(description=True)</div>
<div>#it gives me one confusion matrix which I guess is the mean one over all N folds(?)</div><div><br></div><div>Any hints or help is much appreciated!</div><div><br></div><div>Cheers,</div><div>Patrik</div><div><br></div>
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