On Sat, Jan 21, 2012 at 2:28 AM, Gael Varoquaux
wrote:
> Each discussion on the scipy mailing about matrices versus arrays raises
> a thread expressing incomprehension across different groups of users that
> either think that matrix objects are dangerous and to be avoided, or
> fundamental to exp
On Thu, Jan 19, 2012 at 10:48:11AM -0500, Kenneth C. Arnold wrote:
> As an aside to those who use scipy's sparse matrices: do you find it
> troublesome that scipy's sparse things behave like matrices instead of
> like ndarrays?
Yes I do.
> Of course this should be brought up on a main scipy list,
2012/1/19 Kenneth C. Arnold :
> As an aside to those who use scipy's sparse matrices: do you find it
> troublesome that scipy's sparse things behave like matrices instead of
> like ndarrays? If dense matrices are a thin wrapper around dense
> ndarrays, shouldn't sparse matrices be a thin wrapper ar
On Thu, Jan 19, 2012 at 10:48, Kenneth C. Arnold
wrote:
> On Thu, Jan 19, 2012 at 3:05 AM, Olivier Grisel
> wrote:
>> Rather than improving the error message when passing sparse arrays to
>> the dense impl of SVC we should refactor SVC to accept both dense and
>> sparse representation and use the
On Thu, Jan 19, 2012 at 3:05 AM, Olivier Grisel
wrote:
> Rather than improving the error message when passing sparse arrays to
> the dense impl of SVC we should refactor SVC to accept both dense and
> sparse representation and use the right wrapper as already done for
> SGD, LinearSVC, LogisticReg
2012/1/19 Andreas :
> I'll gladly review your pull request ;)
+1 :)
--
Lars Buitinck
Scientific programmer, ILPS
University of Amsterdam
--
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On 01/19/2012 09:05 AM, Olivier Grisel wrote:
> 2012/1/19 Gael Varoquaux:
>
>> On Thu, Jan 19, 2012 at 12:13:38PM +0900, Mathieu Blondel wrote:
>>
>>> Since your data is sparse, you need to use svm.sparse.SVC, not svm.SVC.
>>>
>> Those error messages are really not enlightning. Ma
2012/1/19 Gael Varoquaux :
> On Thu, Jan 19, 2012 at 12:13:38PM +0900, Mathieu Blondel wrote:
>> Since your data is sparse, you need to use svm.sparse.SVC, not svm.SVC.
>
> Those error messages are really not enlightning. Mathieu, you were saying
> in the thread about GSOC that sparse functionality
On Thu, Jan 19, 2012 at 12:13:38PM +0900, Mathieu Blondel wrote:
> Since your data is sparse, you need to use svm.sparse.SVC, not svm.SVC.
Those error messages are really not enlightning. Mathieu, you were saying
in the thread about GSOC that sparse functionality in the scikit could
use some love.
On Thu, Jan 19, 2012 at 9:57 AM, Manish Katyal wrote:
> Just getting started with scikits and was running into a problem:
>
> My large dataset is in SVMLight format. I load it like (X_train, y_train =
> load_svmlight_file(f))
> When I try using the SVM
> Classifier: svm.SVC(gamma=0.001).fit(X_trai
On 19 January 2012 11:57, Manish Katyal wrote:
> Just getting started with scikits and was running into a problem:
>
> My large dataset is in SVMLight format. I load it like (X_train, y_train =
> load_svmlight_file(f))
> When I try using the SVM
> Classifier: svm.SVC(gamma=0.001).fit(X_train,y_tr
Just getting started with scikits and was running into a problem:
My large dataset is in SVMLight format. I load it like (X_train, y_train =
load_svmlight_file(f))
When I try using the SVM
Classifier: svm.SVC(gamma=0.001).fit(X_train,y_train), I get the following
error:
"File
"/var/tmp/scilearn/l
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