On Tue, Dec 27, 2011 at 6:23 PM, Olivier Grisel <[email protected]> wrote: > Hi all, > > I came across the following blog post about Andrew Ng's ML class and I > like the training / validation errors plots to find out whether the > model is too biased (underfitting) or two lax (high variance, > over-fitting). > > http://digitheadslabnotebook.blogspot.com/2011/12/practical-advice-for-applying-machine.html
I just completed this class. I took detailed notes (many screenshots) for myself on the lessons that offered practical advice. They may be useful to you: https://sites.google.com/a/njwilson.net/ml-class/practical Perhaps I should clean them up and post them for a wider audience... > Has someone tried to apply this trick in practice? Do you think it > would be interesting to provide new utilities to easily draw such > plots as a way to qualitatively check / validate model selection > achieved by automated methods such as grid search CV? I'm quite new to machine learning and haven't had the chance to apply it yet, so I can't comment on these techniques in practice. But as someone who has completed the class and is playing with scikit-learn, I would love to see support for easily generating these plots. Nick Wilson ------------------------------------------------------------------------------ Write once. Port to many. Get the SDK and tools to simplify cross-platform app development. Create new or port existing apps to sell to consumers worldwide. Explore the Intel AppUpSM program developer opportunity. appdeveloper.intel.com/join http://p.sf.net/sfu/intel-appdev _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
