[mlpack-git] [mlpack/mlpack] NeuralEvolution - implemented gene, genome (#686)
Excalibur
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Sun Jul 3 13:33:37 EDT 2016
> + std::sort(depthAndLinks.begin(), depthAndLinks.end());
> +
> + for (ssize_t i=0; i<linkGenesSize; ++i) {
> + aLinkGenes[i] = depthAndLinks[i].link;
> + }
> + }
> +
> + // Activate genome. The last dimension of input is always 1 for bias. 0 means no bias.
> + void Activate(std::vector<double>& input) {
> + assert(input.size() == aNumInput);
> +
> + SortLinkGenes();
> +
> + // Set all neurons' input to be 0.
> + for (ssize_t i=0; i<NumNeuron(); ++i) {
> + aNeuronGenes[i].Input(0);
A recurrent connection's input is the neuron's activation, so I think it won't lose actually.
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