Re: [Scikit-learn-general] poor svm performance

2012-02-15 Thread Mathieu Blondel
> Well, it's a tradeoff: a good reimplementation that would approach the > original in terms of performance is a lot of work. For it to be > sustainable, the team would have to grow a fair amount. It is a lot of work but the bindings have caused us lots of problems so far (memory leaks, sign switc

Re: [Scikit-learn-general] poor svm performance

2012-02-15 Thread Gael Varoquaux
> I say this as someone who probably won't be responsible for doing the > work, so feel free to ignore... > Shouldn't reimplementation be a long term goal for such dependencies?  > This would make it the sklearn way, allowing easier/better changes in > the future. Well, it's a tradeoff:

Re: [Scikit-learn-general] poor svm performance

2012-02-15 Thread Robert Layton
On 16 February 2012 03:24, Olivier Grisel wrote: > 2012/2/15 Ian Goodfellow : > > Indeed, in Coates' code the bias term is not penalized. > > Is there any way to turn off the bias penalty in liblinear? > > Nope. It as been debate before and apparently upstream finds intercept > regularization a r

Re: [Scikit-learn-general] poor svm performance

2012-02-15 Thread Olivier Grisel
2012/2/15 Ian Goodfellow : > Indeed, in Coates' code the bias term is not penalized. > Is there any way to turn off the bias penalty in liblinear? Nope. It as been debate before and apparently upstream finds intercept regularization a reasonable thing to do :) Forking liblinear in scikit-learn to

Re: [Scikit-learn-general] poor svm performance

2012-02-15 Thread Ian Goodfellow
Indeed, in Coates' code the bias term is not penalized. Is there any way to turn off the bias penalty in liblinear? On Wed, Feb 15, 2012 at 3:57 AM, Paolo Losi wrote: > > > On Wed, Feb 15, 2012 at 8:26 AM, Olivier Grisel > wrote: >> >> 2012/2/15 Ian Goodfellow : >> > Further update: I talked to

Re: [Scikit-learn-general] SVC documentation inaccuracy

2012-02-15 Thread Alexandre Gramfort
>> sklearn.svm.enable_libsvm_stdout(True) +1 too A -- Virtualization & Cloud Management Using Capacity Planning Cloud computing makes use of virtualization - but cloud computing also focuses on allowing computing to be

Re: [Scikit-learn-general] SVC documentation inaccuracy

2012-02-15 Thread David Warde-Farley
On 2012-02-15, at 3:16 AM, Olivier Grisel wrote: > sklearn.svm.enable_libsvm_stdout(True) > > WDYT? I'm +1 for what it's worth. David -- Virtualization & Cloud Management Using Capacity Planning Cloud computing makes u

Re: [Scikit-learn-general] OneVsRestClassifier in git master

2012-02-15 Thread David Warde-Farley
On 2012-02-15, at 2:20 AM, Mathieu Blondel wrote: > git bisect tells me that the regression was introduced in: > https://github.com/scikit-learn/scikit-learn/commit/658897497399147a78fad5f7001fc62dd1e487ed Wow, that was quick. Thanks, Mathieu! -

Re: [Scikit-learn-general] poor svm performance

2012-02-15 Thread Paolo Losi
On Wed, Feb 15, 2012 at 8:26 AM, Olivier Grisel wrote: > 2012/2/15 Ian Goodfellow : > > Further update: I talked to Adam Coates and his code doesn't implement > > a standard SVM. Instead it's an "L2 SVM" which squares all the slack > > variables. So this probably explains the difference in perform

Re: [Scikit-learn-general] SVC documentation inaccuracy

2012-02-15 Thread Olivier Grisel
2012/2/15 Alexandre Gramfort : >> Fabian: any idea on how to do that? > > use : > > > libsvm.set_verbosity_wrap(1) > libsvm_sparse.set_verbosity_wrap(1) Thanks. > in svm/base.py > > maybe we could add a verbose flag to SVM estimators. Unfortunately we cannot make it a per-estimator parameter as

Re: [Scikit-learn-general] SVC documentation inaccuracy

2012-02-15 Thread Alexandre Gramfort
> Fabian: any idea on how to do that? use : libsvm.set_verbosity_wrap(1) libsvm_sparse.set_verbosity_wrap(1) in svm/base.py maybe we could add a verbose flag to SVM estimators. Alex -- Virtualization & Cloud Manageme