On 06/06/2013 07:02 AM, Robert Layton wrote:
OK, it's up as PR
https://github.com/scikit-learn/scikit-learn/pull/2037 and ready to go.
Does that still assume a symmetric matrix?
The easy solution to you problem would have been to feed mst + mst.T to
the components algorithm ;)
I fell into
On using the lasso_stability_path, some paths in my feature set have a
bell-curve shape. How should I interpret this?
The real problem is that I don't have a quantitative understanding of this
(yet). Many of my feature sets have the shape shown in the sklearn manual,
but one particular - not so
all,
IN my ubuntu(uname -a): Linux ubuntu 3.2.0-29-generic-pae #46-Ubuntu SMP Fri
Jul 27 17:25:43 UTC 2012 i686 i686 i386 GNU/Linux,
after installing the scikit-learn from source package followd by
https://pypi.python.org/pypi/scikit-learn/ ,
run 'nosetests --exe sklearn' ,following error
could it be that the folder you're in (~/scikit-learn) contains the
scikit-learn sources?
2013/6/6 linxpwww linxp...@163.com
all,
IN my ubuntu(uname -a): Linux ubuntu 3.2.0-29-generic-pae #46-Ubuntu SMP
Fri Jul 27 17:25:43 UTC 2012 i686 i686 i386 GNU/Linux,
after installing the
Hi,
I noticed that GridSearchCV fits a new estimator from scratch for each grid
point. But when working with pipelines where multiple steps have tuning
parameters, some time could be saved by fitting an early step once and then
fitting the later steps along a sequence of grid points while
Using in a clever way a joblib.Memory would be the way I would like to
address this. I have no precise idea on how I would do this, though.
G
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I proposed something that did this among a more general solution for warm
starts without memoizing a couple of weeks ago, but I think memoizing is
neater and handles most cases. To handle it generally, you could add a
memoize parameter to Pipeline. Then I guess you'd have to do some subset of:
*
On Tue, Jun 4, 2013 at 8:16 PM, Peter Prettenhofer
peter.prettenho...@gmail.com wrote:
I believe more in my results than in my expertise - and so should you :-)
**
+1! There's very very few examples of theory trumping data in history...
And a bajillion of the converse.
I also think Joel put
I believe more in my results than in my expertise - and so should you :-)
+1! There's very very few examples of theory trumping data in history... And
a bajillion of the converse.
I guess I didn't express myself clearly: I didn't mean to say that I
mistrust my results per se.. I'm not that
