void NeuralNetwork::FeedForwardNN()
{
	// OBSOLETE
	for (int hiddenIndex = 0; hiddenIndex < m_hiddenLayers->m_neurons.size(); hiddenIndex++)
	{
		double sum = 0;
		for (int index = 0; index < m_inputs->m_neurons.size(); index++)
		{
			sum += (m_inputs->m_neurons.at(index).m_value)*(m_inputs->m_neurons.at(index).m_weights.at(hiddenIndex));
		}
		//sum += m_inputs->m_bias.m_value * m_inputs->m_bias.m_weights.at(hiddenIndex);

		m_hiddenLayers->m_neurons.at(hiddenIndex).m_sumOfPreviousLayer = sum;
		m_hiddenLayers->m_neurons.at(hiddenIndex).m_value = GetActivationValue(sum);
	}

	for (int outputIndex = 0; outputIndex < m_outputs->m_neurons.size(); outputIndex++)
	{
		double sum = 0;
		for (int hiddenIndex = 0; hiddenIndex < m_hiddenLayers->m_neurons.size(); hiddenIndex++)
		{
			sum += (m_hiddenLayers->m_neurons.at(hiddenIndex).m_value)*(m_hiddenLayers->m_neurons.at(hiddenIndex).m_weights.at(outputIndex));
		}

		//sum += m_hiddenLayers->m_bias.m_value * m_hiddenLayers->m_bias.m_weights.at(outputIndex);

		m_outputs->m_neurons.at(outputIndex).m_sumOfPreviousLayer = sum;
		m_outputs->m_neurons.at(outputIndex).m_value = GetActivationValue(sum);
	}
}