[mlpack-git] [mlpack/mlpack] NeuralEvolution - implemented gene, genome (#686)

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Wed Jun 8 09:39:08 EDT 2016


> +
> +      // Loop neurons to calculate neurons' activation.
> +      for (unsigned in j=aNumInput; j<aNeuronGenes.size(); ++j) {
> +        double x = aNeuronGenes[j].aInput;  // TODO: consider bias. Difference?
> +        aNeuronGenes[j].aInput = 0;
> +
> +        double y = 0;
> +        switch (aNeuronGenes[j].Type()) { // TODO: revise the implementation.
> +          case SIGMOID:                   // TODO: more cases.
> +            y = sigmoid(x);
> +            break;
> +          case RELU:
> +            y = relu(x);
> +            break;
> +          default:
> +            y = sigmoid(x);

@zoq I got you point! Seems it is better to use the existing ANN activation functions.

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