Re: [scikit-learn] baggingClassifier with pipeline

You can always add a first step that turns you numpy array into a DataFrame such as the one required afterwards. A bit of object oriented programming might be required though, for deriving you class from BaseTransformer and writing you particular code for fit and transform method. Alternatively you

Re: [scikit-learn] scikit-learn Digest, Vol 30, Issue 25

Good to know! El lun., 8 oct. 2018 9:08, Joel Nothman escribió: > Just a note that multiple layers of stacking can be achieved with > StackingClassifier using nesting. > ___ > scikit-learn mailing list > scikit-learn@python.org > https://mail.python.or

Re: [scikit-learn] scikit-learn Digest, Vol 30, Issue 25

I would propose PipeGraph for stacking, it comes natural and it could help a lot in making things easier for core developers. Disclaimer: I'm coauthor of PipeGraph Manuel Castejón Limas Escuela de Ingenierías Industrial, Informática y Aeroespacial Universidad de León Campus de Vegazana sn. 2

Re: [scikit-learn] [ANN] Scikit-learn 0.20.0

How about a docker based approach? Just thinking out loud Best Manuel El vie., 28 sept. 2018 19:43, Andreas Mueller escribió: > > > On 09/28/2018 01:38 PM, Andreas Mueller wrote: > > > > > > On 09/28/2018 12:10 PM, Sebastian Raschka wrote: > I think model serialization should be a priority.

Re: [scikit-learn] [ANN] Scikit-learn 0.20.0

Huge huge Thank you developers! Keep up the good work! El mié., 26 sept. 2018 20:57, Andreas Mueller escribió: > Hey everbody! > I'm happy to (finally) announce scikit-learn 0.20.0. > This release is dedicated to the memory of Raghav Rajagopalan. > > You can upgrade now with pip or conda! > > Th

[scikit-learn] CircleCI

Dear all, Contrib projects template hints the authors to use TravisCI, CircleCI and Appveyor. Now that CircleCI has moved to version 2, is there any idea on what to do about it? Will the template be updated? Is it ok if we use only CircleCI? What do you, core devs, suggest about that? Best wishes M

Re: [scikit-learn] Delegating "get_params" and "set_params" to a wrapped estimator when parameter is not defined.

Dear Joel, I've changed the code of PipeGraph in order to change the old wrappers to new Mixin Classes. The changes are reflected in this MixinClasses branch: https://github.com/mcasl/PipeGraph/blob/feature/MixinClasses/pipegraph/adapters.py My conclusions are that although both approaches are f

Re: [scikit-learn] Delegating "get_params" and "set_params" to a wrapped estimator when parameter is not defined.

Nope! Mostly because of lack of experience with mixins. I've done some reading and I think I can come up with a few mixins doing the trick by dynamically adding their methods to an already instantiated object. I'll play with that and I hope to show you something soon! Or at least I will have better

Re: [scikit-learn] Delegating "get_params" and "set_params" to a wrapped estimator when parameter is not defined.

Hi Javier! Yo can have a look at: https://github.com/mcasl/PipeGraph/blob/master/pipegraph/adapters.py There are a few adapters there and I had tool deal with that situation. I solved it by using __getattr__ and __setattr__. Best Manolo El vie., 13 abr. 2018 17:53, Javier López escribió: > I h