<ol>
<li>It should be the same dataset. And yes you have to split the last dimension from the training. </li>
<li>Take a look at the constructor of the FNN class:</li>
</ol>

<pre><code>FFN(LayerType &amp;&amp;network,
  OutputType &amp;&amp;outputLayer,
  InitializationRuleType initializeRule = InitializationRuleType(),
  PerformanceFunction performanceFunction = PerformanceFunction());
</code></pre>

<p>The third parameter it the object used to initialize the weights. So in your test you should use that parameter, something like this should work:</p>

<pre><code>KathirvalavakumarSubavathiInitialization initRule(data, 0.3);
FFN&lt;decltype(modules),
    decltype(classOutputLayer),
    KathirvalavakumarSubavathiInitialization,
    PerformanceFunctionType&gt; net(modules, classOutputLayer, initRule);
</code></pre>

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