We cannot use lambda as parameter name because it is a reserved keyword of the python language (for defining anonymous functions). This is why used "alpha" instead of "lambda" for the ElasticNet / Lasso model initially and then this notation was reused in more recently implemented estimators such as SGDClassifier, Ridge and so on to maintain some consistency. In retrospect I would have prefered it named something explicit like "regularization" or "l2_reg" instead of "alpha".
Still I like the (alpha, l1_ratio) parameterization better over the (l2_reg, l1_reg) parameter set as when grid searching it is very likely that keeping l1_ratio around 0.15 will make it possible to reach good results when tuning "alpha" and thus make it possible to grid search only one hyperparams instead of two and make it easier to implement regularization paths with warm restarts. ------------------------------------------------------------------------------ November Webinars for C, C++, Fortran Developers Accelerate application performance with scalable programming models. Explore techniques for threading, error checking, porting, and tuning. Get the most from the latest Intel processors and coprocessors. See abstracts and register http://pubads.g.doubleclick.net/gampad/clk?id=60136231&iu=/4140/ostg.clktrk _______________________________________________ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
