Can you illustrate your use-case Michael?
On 06/25/2015 02:14 PM, Joel Nothman wrote:
As much as possible, parameters to a model should be specified to the
class constructor, not methods, even if application is there. This has
been the scikit-learn design for a while in order to enable things
As much as possible, parameters to a model should be specified to the class
constructor, not methods, even if application is there. This has been the
scikit-learn design for a while in order to enable things like grid search
and a bare-bones pipeline implementation. So external projects adding
addi
As far as I know, there aren't any estimators with predict kwargs. This
doesn't mean that engineers aren't writing their own estimators, which may
need kwargs. To me, one of sklearns great strengths is its pipeline, and
extending its functionality to allow for more flexible estimator methods
seems
What estimators have predict with multiple args? Without support for same
in cross validation routines and scorers, isn't t easier to write this
functionality in custom code as you need it, leaving the predictor off the
Pipeline?
On 25 June 2015 at 06:06, Michael Kneier wrote:
> Hi all,
>
> It d
