[scikit-learn] Opinion on reference mentioning that RF uses weak learners

[Nicolas Hug]

I'm not sure honestly, but I think you'll find more details in 
Schapire's paper (http://rob.schapire.net/papers/strengthofweak.pdf) and 
its refs. In particular page 5 (201)

On 8/16/20 8:37 PM, Brown J.B. via scikit-learn wrote:
> > As previously mentioned, a "weak learner" is just a learner that 
> barely performs better than random.
>
> To continue with what the definition of a random learner refers to, 
> does it mean the following contexts?
> (1) Classification: a learner which uniformly samples from one of the 
> N endpoints in the training data (e.g., the set of unique values in 
> the response vector "y").
> (2) Regression: a learner which uniformly samples from the range of 
> values in the endpoint/response vector (e.g., uniform sampling from 
> [min(y), max(y)]).
>
> Should even more context be explicitly declared (e.g., not uniform 
> sampling but any distribution sampler)?
>
> J.B.
>
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