Hi Yarick, thanks for chiming in! I thought about spamming the pymvpa
list, but figured one at a time :)
The scikit-learn LogisticRegression class uses one-vs-all in a
multiclass setting, although I also tried it with their one-vs-one
metaclassifier with similar "weird" results.
Interestingly, th
just to educate myself -- how sklearn does multiclass decisions in this
case? if it is all pairs classification + voting, then the answer is
simple -- ties, and the "first one in order" would take all those.
but if there is no ties involved then, theoretically (since not sure if it is
applicable
Hi Folks,
I hope you don't mind a question that's a mix of general machine
learning and scikit-learn. I'm happy to kick it over to metaoptimize,
but I'm not 100% sure I'm doing everything "right" from a scikit-learn
perspective so I thought it best to ask here first.
I'm doing classification of f
2012/1/28 Mathias Verbeke :
> Hi Oliver,
>
> Thanks, that works! Sorry for the dummy questions.
No pbm, the error message was confusing. Now that the 2 classes are
merged users will no longer run in this kind of recurring issue in
future releases.
--
Olivier
http://twitter.com/ogrisel - http://g
Hi Oliver,
Thanks, that works! Sorry for the dummy questions.
Cheers and thanks again,
Mathias
On Sat, Jan 28, 2012 at 12:38 PM, Olivier Grisel
wrote:
> 2012/1/28 Mathias Verbeke :
> > Hi Gael,
> >
> > Thanks for your quick answer. Your solution solved the error, but now I
> get
> > this:
> >
On Fri, Jan 27, 2012 at 12:32:31PM -0800, Fernando Perez wrote:
> And just to state what is probably obvious, we're more than happy to
> adjust the apis in ipython as necessary to reduce the impedance
> mismatches between tools.
I think that we share the same view: as much parallel code as possib
2012/1/28 Mathias Verbeke :
> Hi Gael,
>
> Thanks for your quick answer. Your solution solved the error, but now I get
> this:
>
> Traceback (most recent call last):
> File "./svm_sklearn.py", line 43, in
> train(training_set_file_name, model_file_name)
> File "./svm_sklearn.py", line 17,
Hi Gael,
Thanks for your quick answer. Your solution solved the error, but now I get
this:
Traceback (most recent call last):
File "./svm_sklearn.py", line 43, in
train(training_set_file_name, model_file_name)
File "./svm_sklearn.py", line 17, in train
clf.fit(X_train, y_train)
Fil
On Sat, Jan 28, 2012 at 09:47:56AM +0100, Mathias Verbeke wrote:
> sklearn.linear_model.sgd_fast_sparse
> (sklearn/linear_model/sgd_fast_sparse.c:5701)
> ImportError: No module named sklearn.linear_model.sgd_fast
I think that your scikit install wasn't built properly. How do you
install it? Could
