Comments (18)
Sure I will do it.
from lightning.
Thanks. I am extensively using lightning with some industrial partners and one of the complications we faced was building on Windows. We solved the problem and I managed to do some conda packages (https://anaconda.org/fabianp/lightning). All is fine but it will be difficult to track versions since lightning has always been on v0.1-git. It would help if we start releasing versions from time to time. I am willing to help as much as I can with this. What do you think?
from lightning.
With your increased involvement in lightning, it would be nice to move the project to a github organization. We can also move the webpage to github. Regarding releases, I had been avoiding them but if you're willing to do them... :)
Regarding the organization, @vene and I had been discussing the idea of a "scikit-learn-contrib" or "scikit-learn-universe" organization where to put various scikit-learn compatible projects. lightning could possibly be moved there. Or we can create our own organization too.
from lightning.
yes to all! As for my involvement, yes, I plan to heavily rely on lightning within the next months, so at least for the close future I will volunteer to maintain it.
I really think releases would positively impact the package quality. However, one problem I foresee is that the pypi page is taken (https://pypi.python.org/pypi/Lightning) :-(
from lightning.
Very cool, I will try my best to help!
from lightning.
I tried to rebuild the docs but the class references don't display properly. I suspect a bug in sphinx-bootstrap-theme, which lightning currently depends on.
https://pypi.python.org/pypi/sphinx-bootstrap-theme/
I guess it's better to work on scikit-learn-contrib's documentation template then use it for lightning.
from lightning.
I proposed a fix in PR #56 . The references seem to work fine for me with this patch.
from lightning.
Great, thanks! Feel free to create the scikit-learn-contrib.github.io repo and move the documentation in the lightning/ folder.
from lightning.
Done! http://scikit-learn-contrib.github.io/lightning/ :-)
from lightning.
@ogrisel Could you take care of pointing contrib.scikit-learn.org to github? Thanks in advance!
from lightning.
@GaelVaroquaux @ogrisel Do you have the privileges to point contrib.scikit-learn.org to github's servers or should I ask Stéfan van der Walt?
from lightning.
I think I can do that, let me check.
from lightning.
This PR needs to be merged scikit-learn-contrib/scikit-learn-contrib.github.io#1
from lightning.
@ogrisel Merged.
By the way, your invitation to scikit-learn-contrib still appears as pending. Did you receive the email? If not I will send it to you again.
from lightning.
Joined. The CNAME is in place: http://contrib.scikit-learn.org/lightning/
but there is no top level index: http://contrib.scikit-learn.org/
from lightning.
Works on my side too. Thanks a lot!
from lightning.
I added a temporary index.html.
@fabianp Please update your blog with lightning's new fancy URL :)
from lightning.
cool, done!
from lightning.
Related Issues (20)
- Unsafe screening with CDClassifier? HOT 1
- Forgotten intercept in SGDRegressor HOT 2
- ModuleNotFoundError: No module named 'sklearn.externals.six' HOT 4
- How to pip sklearn-contrib-lightning HOT 2
- 2d errors when passing pandas DataFrame/Series
- Nonnegative penalties actually allowed in CDRegressors HOT 3
- FistaRegressor does not converge for real data HOT 3
- build pb on python 3.9 HOT 1
- Change assert imports HOT 2
- do you have Quantile Regression for spars data after one hot transformation
- do you have Regression for spars categorical big data after one hot transformation
- do you have support vector regression with soft margin and confidence interval ?
- do you have implementation for regression with confidence intervals ?
- Does lightning natively support multi-label HOT 1
- DOC: sometimes the Lasso solution is the same as sklearn, sometimes not HOT 5
- install help
- ENH - Add support of intercept in ``SDCARegressor`` HOT 1
- Why not initialize SAG/SAGA memory with 0 and divide by seen indices so far as in sklearn?
- Missing Support for class-weights specifications to tacke Disproportionate Number of Samples between dependent variable classes
- CDClassifier : error for penalty="l1" and penalty="l2", but no error for penalty="l1/l2" HOT 5
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from lightning.