Hi,
There is the orthogonal matching pursuit algorithm (an another CS
algorithm) in scikit-learn which is classified as a regression model.
The notations are a bit different from the CS community.
Arnaud Joly
Le 28/11/2012 08:38, [email protected] a écrit :
Hi Meng:
It is a compressive sensing method. Which serves as reconstruct signal
from indeterminacy sensing data:
Y = Phi * x + n
Where Phi is a N*M matrix with N much less than M.
Sorry for my English.
:)
Liu benyuan
? 2012-11-28,15:13,xinfan meng <[email protected]
<mailto:[email protected]>> ??:
You can first take a look at this page:
http://scikit-learn.org/stable/developers/index.html .
As to the model, is it a classification / clustering / factorization
algorithm or something?
On Wed, Nov 28, 2012 at 3:08 PM, <[email protected]
<mailto:[email protected]>> wrote:
Dear scikit-learn community:
Block Sparse Bayesian Learning is a powerful CS algorithm for recovering
block sparse signals with structures, and shows the additional benefits of
reconstruct non-sparse signals, see Dr. zhilin zhang's websites:
http://dsp.ucsd.edu/~zhilin/BSBL.html
<http://dsp.ucsd.edu/%7Ezhilin/BSBL.html>
I currently implement the BSBL-BO algorithm by Zhang and a fast version of
BSBL algorithm recently proposed by us, called BSBL-FM, in python. Plus many
demos using these two codes. Does scikit-learn community welcome such type of
code ? what is the procedure to submit the code in the mainstream of scikit
learn?
Thanks for the great project!
Liu benyuan
------------------------------------------------------------------------------
Keep yourself connected to Go Parallel:
INSIGHTS What's next for parallel hardware, programming and
related areas?
Interviews and blogs by thought leaders keep you ahead of the curve.
http://goparallel.sourceforge.net
_______________________________________________
Scikit-learn-general mailing list
[email protected]
<mailto:[email protected]>
https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
--
Best Wishes
--------------------------------------------
Meng Xinfan(???)
Institute of Computational Linguistics
Department of Computer Science & Technology
School of Electronic Engineering & Computer Science
Peking University
Beijing, 100871
China
------------------------------------------------------------------------------
Keep yourself connected to Go Parallel:
INSIGHTS What's next for parallel hardware, programming and related
areas?
Interviews and blogs by thought leaders keep you ahead of the curve.
http://goparallel.sourceforge.net
_______________________________________________
Scikit-learn-general mailing list
[email protected]
<mailto:[email protected]>
https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
------------------------------------------------------------------------------
Keep yourself connected to Go Parallel:
INSIGHTS What's next for parallel hardware, programming and related areas?
Interviews and blogs by thought leaders keep you ahead of the curve.
http://goparallel.sourceforge.net
_______________________________________________
Scikit-learn-general mailing list
[email protected]
https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
------------------------------------------------------------------------------
Keep yourself connected to Go Parallel:
INSIGHTS What's next for parallel hardware, programming and related areas?
Interviews and blogs by thought leaders keep you ahead of the curve.
http://goparallel.sourceforge.net
_______________________________________________
Scikit-learn-general mailing list
[email protected]
https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
