@Alexandre, @Mathieu: Thanks for these hints. I'll give it a try.
So setting epsilon=0 and C to a large value should result in a
regression in the L1 norm with almost no regularization of w, right?.
One thing that just crossed my mind. Would it be possible in a linear
SVR setting to let the
On Mon, Jan 13, 2014 at 5:09 PM, florian.wilh...@gmail.com
florian.wilh...@gmail.com wrote:
So setting epsilon=0 and C to a large value should result in a
regression in the L1 norm with almost no regularization of w, right?.
One thing that just crossed my mind. Would it be possible in a
Here's an example that illustrates the use of LinearSVR for doing robust
regression with lightning:
https://github.com/mblondel/lightning/blob/master/examples/plot_robust_regression.py
Regarding epsilon=0, it is a good choice for LinearSVR but less so for
(kernel) SVR. epsilon=0 leads to
Hi,
at Blue Yonder we often use Scikit-Learn but are sometimes missing
more robust regression methods that are not based on the L2 norm.
So far I only knew Theil-Sen as a linear regression method with only a
single explanatory variable. The work of Xin Dang, Hanxiang Peng,
Xueqin Wang and Heping
hi,
did you try SVR ? eventually setting epsilon to 0.?
if it's too slow have a look at lightning new LinearSVR estimator.
Alex
On Sat, Jan 11, 2014 at 7:28 PM, florian.wilh...@gmail.com
florian.wilh...@gmail.com wrote:
Hi,
at Blue Yonder we often use Scikit-Learn but are sometimes
Hi,
I'd like to add a Theil-Sen estimator for a multiple linear regression
problem to Scikit-Learn as described in the paper:
http://home.olemiss.edu/~xdang/papers/MTSE.pdf
Is anyone already working on this or are there any objections
regarding the inclusion of a Theil-Sen estimator into
Hi,
There have been some implementations of Theil-Sen floating around for inclusion
in statsmodels, but no PRs yet. IMO it might fit in a little better in
statsmodels.robust than sklearn unless their are some aspects of Theil-Sen I'm
not familiar with.
Skipper
Sent from my mobile
On Jan
