Hey Ariel, On Sat, Sep 29, 2012 at 08:54:46AM -0700, Ariel Rokem wrote: > Sure - here's a minimal example based on what I'm trying to do with this (data > at the top, calculations at the bottom):
> https://gist.github.com/3804428 I do believe that it's a convergence problem. I have updated your gist at https://gist.github.com/3804487 to fit with more and more iterations, and when I run it I get: In [1]: %run sklearn_EN_example.py /home/varoquau/dev/scikit-learn/sklearn/linear_model/coordinate_descent.py:207: UserWarning: Coordinate descent with alpha=0 may lead to unexpected results and is discouraged. self.positive) /home/varoquau/dev/scikit-learn/sklearn/linear_model/coordinate_descent.py:222: UserWarning: Objective did not converge for target 0, you might want to increase the number of iterations ' to increase the number of iterations') With ElasticNet: 0.9785 With ElasticNet (1 refit): 0.9800 With ElasticNet (2 refit): 0.9809 With ElasticNet (3 refit): 0.9815 With ElasticNet (4 refit): 0.9819 With ElasticNet (5 refit): 0.9821 With ElasticNet (6 refit): 0.9823 With ElasticNet (7 refit): 0.9824 With ElasticNet (8 refit): 0.9825 With ElasticNet (9 refit): 0.9826 With ElasticNet (10 refit): 0.9827 With LinearRegression: 1.0000 So the conclusion are indeed that ElasticNet with alpha=0 does not converge well, as we thought. Also, the code did warn you about the problem. The coordinate descent solver does not work well on unpenalized problem. You should not use it. It's a fundemental flaw of the algorithm. One algorithm cannot be well-suited for every usecase. The coordinate descent solver used in the ElasticNet object is good for non-smooth problems (the l1 penalty) with sparse solutions. While this is the normal setting for Elastic Net, you are definitely not in this situation. HTH, Gaël ------------------------------------------------------------------------------ How fast is your code? 3 out of 4 devs don\\\'t know how their code performs in production. Find out how slow your code is with AppDynamics Lite. http://ad.doubleclick.net/clk;262219672;13503038;z? http://info.appdynamics.com/FreeJavaPerformanceDownload.html _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
