<p>In <a href="https://github.com/mlpack/mlpack/pull/686#discussion_r66709850">src/mlpack/tests/ne_test.cpp</a>:</p>
<pre style='color:#555'>> + LinkGene link3(2, 3, 0, 0);
> + LinkGene link4(0, 4, 0, 0);
> + LinkGene link5(1, 4, 0, 0);
> + LinkGene link6(2, 4, 0, 0);
> + LinkGene link7(4, 3, 0, 0);
> +
> + linkGenes.push_back(link1);
> + linkGenes.push_back(link2);
> + linkGenes.push_back(link3);
> + linkGenes.push_back(link4);
> + linkGenes.push_back(link5);
> + linkGenes.push_back(link6);
> + linkGenes.push_back(link7);
> +
> + Genome seedGenome = Genome(0, neuronGenes, linkGenes, numInput, numOutput, depth, fitness);
> +
</pre>
<p>I think it would be a good idea to set a default initial genome inside the CNE method. The authors start with a genome where each input unit is connected with the output units. But, we could also use a hidden units as you did. This way, we can directly start by evolving the network.</p>
<p style="font-size:small;-webkit-text-size-adjust:none;color:#666;">—<br />You are receiving this because you are subscribed to this thread.<br />Reply to this email directly, <a href="https://github.com/mlpack/mlpack/pull/686/files/65f093daf32f6cb353cd6b9304bab88a5e096fdc#r66709850">view it on GitHub</a>, or <a href="https://github.com/notifications/unsubscribe/AJ4bFPDEni05XIbB5VogATS4Wls-0iGrks5qKv7fgaJpZM4IwJa6">mute the thread</a>.<img alt="" height="1" src="https://github.com/notifications/beacon/AJ4bFO9rtoHBvbGapLPc5T8AwtBFUejcks5qKv7fgaJpZM4IwJa6.gif" width="1" /></p>
<div itemscope itemtype="http://schema.org/EmailMessage">
<div itemprop="action" itemscope itemtype="http://schema.org/ViewAction">
<link itemprop="url" href="https://github.com/mlpack/mlpack/pull/686/files/65f093daf32f6cb353cd6b9304bab88a5e096fdc#r66709850"></link>
<meta itemprop="name" content="View Pull Request"></meta>
</div>
<meta itemprop="description" content="View this Pull Request on GitHub"></meta>
</div>