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