Hi,
I took a look at the code
https://github.com/lisitsyn/tapkee_jmlr_benchmarks/blob/master/scikit-learn/sklearn/svm/liblinear.pyx
there are things such as bias in the parameter list. But this is not available
when calling linearSVC. What does it correspond to?
Also, I don’t believe default parameters are used. Epsilon is 1e-4 by default
in sklearn, but 0.1 in liblinear.
And how are fit_intercept and intercept_scaling passed to liblinear?
Please, let me know,
Thank you,
From: Manoj Kumar [mailto:[email protected]]
Sent: Wednesday, August 06, 2014 6:54 PM
To: [email protected]
Subject: Re: [Scikit-learn-general] mapping liblinear wrapper with LinearSVC
Hi,
It looks to me that only the bias parameter is passed to liblinear. It is set
to self.intercept_scaling if fit_intercept is set to True and -1 otherwise. The
rest (I think) are default parameters.
You can have a look at the function signature of train_wrap in liblinear.pyx in
order to clarify this.
On Wed, Aug 6, 2014 at 9:51 PM, Pagliari, Roberto
<[email protected]<mailto:[email protected]>> wrote:
Probably my question was not clear.
What I meant to ask is this: when using sklearn iblinear with default
parameters, what would be the options passed to liblinear library for training,
which is the “options” field in liblinear python wrapper?
Thank you!
From: Pagliari, Roberto
[mailto:[email protected]<mailto:[email protected]>]
Sent: Tuesday, August 05, 2014 4:53 PM
To:
[email protected]<mailto:[email protected]>
Subject: [Scikit-learn-general] mapping liblinear wrapper with LinearSVC
I went through the documentation of the python wrapper for liblinear.
There are a few parameters such as
-p epsilon
-e epsilon (with –s)
-B bias
Assuming I’m using the default value of 1e-4 in sklearn, which values are used
for the parameters above. Does sklearn use default values, or different values?
Thank you,
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Regards,
Manoj Kumar,
GSoC 2014, Scikit-learn
Mech Undergrad
http://manojbits.wordpress.com
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