Hi Federico, no not yet - I just approached them recently regarding this issue - I let you know as soon as I hear from them.
best, Peter 2012/7/10 federico vaggi <[email protected]>: > Peter - did you get any updates from Kaggle? If not, is there anything that > we as a community can do to sway them? > > > On Sat, Jul 7, 2012 at 7:46 PM, Emanuele Olivetti <[email protected]> > wrote: >> >> On 07/05/2012 04:37 PM, Olivier Grisel wrote: >> > 2012/7/5 Emanuele Olivetti <[email protected]>: >> >> On 07/05/2012 08:49 AM, Olivier Grisel wrote: >> >>> 2012/7/5 Peter Prettenhofer <[email protected]>: >> >>>> ... >> >>>> >> >>>> I've to check with the competition organizers whether its ok to put >> >>>> the source code on github - I'll keep you posted. >> >>> If so that would be a great blog post topic. Looking forward to it. >> >>> >> >> Hi, >> >> >> >> For what it's worth, I've put the code of my best submission on >> >> github: >> >> https://github.com/emanuele/kaggle_ops >> >> >> >> http://www.kaggle.com/c/online-sales/forums/t/2136/the-code-of-my-best-submission >> >> >> >> You can download and run it to get an actual file to submit to the >> >> competition. >> >> >> >> Of course I just ranked 21st on that competition so it is *far* less >> >> interesting than >> >> Peter's code :-D, and I've spent only a few hours in recent weekends. >> >> It was >> >> more a proof of concept about using blending, gradient boosting and >> >> joblib than a >> >> serious attempt. >> >> >> >> The resulting code is pretty short: 150 lines to process the dataset >> >> and 80 lines to compute predictions. No real model selection :P >> >> Anyway the code is general and you can put RF or else inside. >> > Thank you very much Emanuele, the blending code is very useful. >> > >> > You should blog it IMHO by explaining the various code snippets: >> > >> > - feature extraction / expansions (e.g. how to handle dates & times as >> > features) >> > - your visual exploration of which feature to convert to the log scale >> > - dealing with missing values >> > - blending the outcome of randomized models >> > - cross validation and performance evaluation in general (did you do >> > any error analysis, e.g. bias and variance using learning curves?) >> > >> > It would be great to turn it the blending procedure as either an >> > example for scikit-learn (using one of the default toy datasets) or a >> > new meta-estimator in a new package (more work required but would >> > improve re-usability). >> > >> > The feature extraction module would also deserve some utility helpers >> > to deal with dates. >> > >> >> I agree with you that I should write more information about the snippets. >> Time is always shorter than necessary though :-/ >> >> I'll try to do my best for the near future, but I'm not promising now ;-) >> Of course if someone wants to do that I'll be happy to provide some >> support :-) >> >> To answer your question: I did just minimal model selection initially, >> but mainly in an incorrect way. Doing things as Peter did requires >> time I don't have at the moment (and maybe skills too!). And I did not >> play much with learning curves as well. Next time maybe! :-) >> >> For now I hope the code is enough. At least it can be run, read and >> of course modified. >> >> Best, >> >> Emanuele >> >> >> ------------------------------------------------------------------------------ >> Live Security Virtual Conference >> Exclusive live event will cover all the ways today's security and >> threat landscape has changed and how IT managers can respond. Discussions >> will include endpoint security, mobile security and the latest in malware >> threats. http://www.accelacomm.com/jaw/sfrnl04242012/114/50122263/ >> _______________________________________________ >> Scikit-learn-general mailing list >> [email protected] >> https://lists.sourceforge.net/lists/listinfo/scikit-learn-general > > > > ------------------------------------------------------------------------------ > Live Security Virtual Conference > Exclusive live event will cover all the ways today's security and > threat landscape has changed and how IT managers can respond. Discussions > will include endpoint security, mobile security and the latest in malware > threats. http://www.accelacomm.com/jaw/sfrnl04242012/114/50122263/ > _______________________________________________ > Scikit-learn-general mailing list > [email protected] > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general > -- Peter Prettenhofer ------------------------------------------------------------------------------ Live Security Virtual Conference Exclusive live event will cover all the ways today's security and threat landscape has changed and how IT managers can respond. Discussions will include endpoint security, mobile security and the latest in malware threats. http://www.accelacomm.com/jaw/sfrnl04242012/114/50122263/ _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
