Hi Andy, In this competition, it helped me get to 1st place for a bit, and the current 1st place holder is also using this. https://www.kaggle.com/c/sf-crime/forums/t/15836/predicting-crime-categories-with-address-featurization-and-neural-nets
I am pretty sure that the data is public for this specific case. I've implemented it in pandas, but the code can definitely use some cleanup and speed up. One of the issues that I would like to clarify a bit better is the data leakage issue, that can be dealt with by adding a bit of laplacian noise. Cheers, CFP On Fri, Sep 18, 2015 at 8:39 PM, Andy <t3k...@gmail.com> wrote: > Hi. > I think it would be great to add this transformation, it has been widely > advertised by Owen. > It would be great to have some public datasets (well-established > preferable) to demonstrate the usefulness. > The sf-crime is public, so that would be a good first step. > Can you provide a full-fledged example? > > Cheers, > Andy > > > On 09/17/2015 07:41 PM, Christos F. Papadopoulos wrote: > > Hi all! > > Are there any plans to implement something like a countfeaturizer? > https://msdn.microsoft.com/en-us/library/azure/dn913056.aspx > > It is a generic method for feature extraction that encodes multi-valued > features based on classification > count data. > I've found it very useful, for example on this kaggle competition: > https://www.kaggle.com/c/sf-crime > > > Thank you! > > > ------------------------------------------------------------------------------ > > > > _______________________________________________ > Scikit-learn-general mailing > listScikit-learn-general@lists.sourceforge.nethttps://lists.sourceforge.net/lists/listinfo/scikit-learn-general > > > > > ------------------------------------------------------------------------------ > > _______________________________________________ > Scikit-learn-general mailing list > Scikit-learn-general@lists.sourceforge.net > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general > >
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