[mlpack-git] [mlpack/mlpack] CNE algorithm (#753)

[Marcus Edel]

> +#include "species.hpp"
> +#include "tasks.hpp"
> +#include "parameters.hpp"
> +
> +namespace mlpack {
> +namespace ne {
> +
> +/**
> + * This class implements Conventional Neuro-evolution (CNE): weight
> + * evolution on topologically fixed neural networks.
> + */
> +template<typename TaskType>
> +class CNE {
> + public:
> +  // Parametric constructor.
> +  CNE(TaskType task, Genome& seedGenome, Parameters& params) {

I agree, that for some methods you have to specify a bunch of parameters, so I think the parameter class comes in handy. On the other side, I like to provide a constructor that works right out of the box and starts with some reasonable parameters. I think in the case of the CNE method, we can specify such parameters. Maybe we can provide an constructor for such a situation, what do you think?


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