[scikit-learn] Delegating "get_params" and "set_params" to a wrapped estimator when parameter is not defined.
t3kcit at gmail.com
Fri Apr 13 12:50:04 EDT 2018
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I'm not sure if ValueError is the right error that would be raised (I
think it's not).
And it's hard to say if this will break something in some edge cases. I
probably rather explicitly encode the parameters of FancyEstimator
instead of the try,
or get them using super.get_params. You also should rewrite get_params.
In principle something like that should work, but I wouldn't go as far
as saying it's
"safe" and you should test it extensively.
On 04/13/2018 12:41 PM, Javier López wrote:
> Is something like this safe, or might I be breaking some important
> def set_params(self, **params):
> super(FancyEstimator, self).set_params(**params)
> except ValueError:
> On Fri, Apr 13, 2018 at 5:05 PM Andreas Mueller <t3kcit at gmail.com
> <mailto:t3kcit at gmail.com>> wrote:
> You just need to implement get_params and set_params yourself to
> delegate in this way, right?
> On 04/13/2018 11:51 AM, Javier López wrote:
>> I have a class
>> `FancyEstimator(BaseEstimator, MetaEstimatorMixin): ...` that wraps
>> around an arbitrary sklearn estimator to add some functionality I
>> am interested about.
>> This class contains an attribute `self.estimator` that contains
>> the wrapped estimator.
>> Delegation of the main methods, such as `fit`, `transform` works
>> just fine, but I am
>> having some issues with `get_params` and `set_params`.
>> The main idea is, I would like to use my wrapped class as a
>> drop-in replacement for
>> the original estimator, but this raises some issues with some
>> that try using the `get_params` and `set_params` straight in my
>> class, as the original
>> parameters now have prefixed names (for instance
>> `estimator__verbose` instead of `verbose`)
>> I would like to delegate calls of set_params and get_params in a
>> smart way so that if a
>> parameter is unknown for my wrapper class, then it automatically
>> goes looking for it in
>> the wrapped estimator.
>> I am not concerned about my class parameter names as there are
>> only a couple of very
>> specific names on it, so it is safe to assume that any unknown
>> parameter name should
>> refer to the base estimator. Is there an easy way of doing that?
>> scikit-learn mailing list
>> scikit-learn at python.org <mailto:scikit-learn at python.org>
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