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

[Marcus Edel]

> +        int fromNeuronIdx = GetNeuronIndex(aLinkGenes[i].FromNeuronId());
> +        double input = aNeuronGenes[toNeuronIdx].Input() + 
> +                       aNeuronGenes[fromNeuronIdx].Activation() * aLinkGenes[i].Weight();
> +        aNeuronGenes[toNeuronIdx].Input(input);
> +        
> +        if (i == NumLink() - 1) {
> +          aNeuronGenes[toNeuronIdx].CalcActivation();
> +        } else if (GetNeuronIndex(aLinkGenes[i + 1].ToNeuronId()) != toNeuronIdx) {
> +          aNeuronGenes[toNeuronIdx].CalcActivation();
> +        }
> +      }
> +    }
> +  }
> +
> +  // Get output vector.
> +  void Output(std::vector<double>& output) {

I suggest to use arma::vec for the output, in this case, we can use a bunch of mlpack methods that can directly work with the output, what do you think? The same applies to the input. E.g. we could directly use PCA to preprocess the input. Also, we could allocate the memory once, and overwrite the results in every iteration instead of clearing the vector.

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