Allow hyper-parameter tuning for immutable models.

[ablaom]

Some context: JuliaML/TableTransforms.jl#67

I don't think this would be too bad, and useful preparation for making the MLJ model interface more flexible later.

The MLJTuning API doesn't really touch on this point. A tuning strategy needs to implement a models method to generate models to evaluate, but doesn't say how the models are generated. They needn't be mutations of a single object. However, the MLJ model interface currently states that models must be mutable, so some tuning strategies do use mutation to generate their models.

TODO:

• To see if the change would be breaking, update this table:

tuning strategy	assumes model types are mutable	pkg providing strategy
Grid	yes	MLJTuning
RandomSearch	yes	MLJTuning
LatinHypercube	yes	MLJTuning.jl
MLJTreeParzenTuning()	?	TreeParzen.jl
ParticleSwarm	?	MLJParticleSwarmOptimization.jl
AdaptiveParticleSwarm	?	MLJParticleSwarmOptimization.jl
Explicit()	no	MLJTuning.jl

cc @juliohm