For ONNX you may be interested in https://github.com/onnx/onnxmltools -
which supports conversion of a few skelarn models to ONNX already.
However as far as I am aware, none of the ONNX backends actually support
the ONNX-ML extended spec (in open-source at least). So you would not be
able to
The ONNX-approach sounds most promising, esp. because it will also allow
library interoperability but I wonder if this is for parametric models only and
not for the nonparametric ones like KNN, tree-based classifiers, etc.
All-in-all I can definitely see the appeal for having a way to export
On Tue, Oct 2, 2018 at 5:07 PM Gael Varoquaux
wrote:
> The reason that pickles are brittle and that sharing pickles is a bad
> practice is that pickle use an implicitly defined data model, which is
> defined via the internals of objects.
>
Plus the fact that loading a pickle can execute
Le 02/10/2018 à 16:46, Andreas Mueller a écrit :
> Thank you for your feedback Alex!
Thanks for answering !
>
> On 10/02/2018 09:28 AM, Alex Garel wrote:
>>
>> * chunk processing (kind of handling streaming data) : when
>> dealing with lot of data, the ability to fit_partial, then use
>>
