sklearn Pipeline decorators
Hi, sklearn Pipelines are awesome, I use them all the time for everything. I've been writing a lot custom transformers lately, and since most of my transformers require no fitting (e.g. replacing all number with "{NUM}" token), I started using transformers as decorators. See snippet (example usage at the end): https://github.com/urigoren/decorators4DS/blob/master/decorators4DS/sklearn_... Do you think this kind of addition should be a part of sklearn ? -- *Uri Goren,* *Phone: +972-507-649-650* *EMail: uri@goren4u.com <uri@goren4u.com>* *Linkedin: il.linkedin.com/in/ugoren/ <http://il.linkedin.com/in/ugoren/>*
That's a cool trick but I am worried it would render our API too "frameworky" for my taste. I think the FunctionTransformer is enough: http://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.Funct...
participants (2)
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Olivier Grisel -
Uri Goren