Ok, sorry! The cost function is embedded into the C smo() function. I
think that you cannot access it directly.
Matthieu Brucher ha scritto:
> Well this is an input parameter, I'd like to access the cost function
> directly so that I can use it to follow its gradient to the limit
> between the
Well this is an input parameter, I'd like to access the cost function
directly so that I can use it to follow its gradient to the limit between
the two classes.
Matthieu
2008/2/15, Davide Albanese <[EMAIL PROTECTED]>:
>
> Yes: https://mlpy.fbk.eu/wiki/MlpyExamplesWithDoc
>
> * svm()
> Initialize
Yes: https://mlpy.fbk.eu/wiki/MlpyExamplesWithDoc
* svm()
Initialize the svm class.
Inputs:
...
cost - for cost-sensitive classification [-1.0, 1.0]
Matthieu Brucher ha scritto:
> OK, I'll try it then :)
>
> Is there an access to the underlying cost function
OK, I'll try it then :)
Is there an access to the underlying cost function ? (this is mainly what I
need)
Matthieu
2008/2/15, Davide Albanese <[EMAIL PROTECTED]>:
>
> I don't know very well libsvm too, the core of svm-mlpy is written in C
> and was developed by Stefano Merler ([EMAIL PROTECTED])
I don't know very well libsvm too, the core of svm-mlpy is written in C
and was developed by Stefano Merler ([EMAIL PROTECTED]).
I have simply wrapped it into svm() Python class.
Regards,
/* da */
Matthieu Brucher ha scritto:
> Thanks for the reference :)
>
> I should have asked in other terms :
Thanks for the reference :)
I should have asked in other terms : how does it compare to libsvm, which is
one of the most known packages for SVMs ?
Matthieu
2008/2/15, Davide Albanese <[EMAIL PROTECTED]>:
>
> Dear Matthieu,
> I don't know very well scikit.
> The Svm is implemented by Sequential M
Dear Matthieu,
I don't know very well scikit.
The Svm is implemented by Sequential Minimal Optimization (SMO).
As for Terminated Ramps (TR) you can read this paper:
/S. Merler and G. Jurman/* Terminated Ramp - Support Vector Machine: a
nonparametric data dependent kernel* Neural Network, 19(10), 1
No, it isn't, a new name to PyML, it is a new project.
Thank you for your advice!
Regards,
/* da */
dmitrey ha scritto:
> isn't MLPY a new name to PyML?
> http://mloss.org/software/view/28/
>
> if no, I guess you'd better add link to your software to
> http://mloss.org/software/
> ("mloss" is "ma
Hi,
How does it compare to the elarn scikit, especially for the SVM part ? How
was it implemented ?
Matthieu
2008/2/14, Davide Albanese <[EMAIL PROTECTED]>:
>
> *Machine Learning Py* (MLPY) is a *Python/NumPy* based package for
> machine learning.
> The package now includes:
>
> * *Support V
isn't MLPY a new name to PyML?
http://mloss.org/software/view/28/
if no, I guess you'd better add link to your software to
http://mloss.org/software/
("mloss" is "machine learning open source software")
Regards, D.
Davide Albanese wrote:
> *Machine Learning Py* (MLPY) is a *Python/NumPy* based pa
*Machine Learning Py* (MLPY) is a *Python/NumPy* based package for
machine learning.
The package now includes:
* *Support Vector Machines* (linear, gaussian, polinomial,
terminated ramps) for 2-class problems
* *Fisher Discriminant Analysis* for 2-class problems
* *Iterative Rel
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