How to use a dataset in Neural Network training
<p>I am trying to implement a Neural Network. I am currently working on the backpropagation part. I don't need help with the coding. I have wrote the feedForward part so far with great success. But my question more related to the dataset I am using. </p>

<p>this is my data set:</p>

<p><a href="http://archive.ics.uci.edu/ml/machine-learning-databases/cpu-performance/machine.data" rel="nofollow noreferrer">http://archive.ics.uci.edu/ml/machine-learning-databases/cpu-performance/machine.data</a></p>

<p>I have to use a 5-fold cross validation to backpropagate and stop training until error threshold is <code>.1</code>, <code>.01</code>, <code>.001</code> meaning I have to do 3 trials. Ignore the first 2 point for each data point. I have already normalized the set. The architecture of the network is 7 neuron in input layer, 3 neurons in 1 hidden layer and 1 output. Very basic implementation.</p>

<p>So my question is,</p>

<ol>
<li><p>I have to break the set up in 5 smaller subset right? keep one for testing and rest for validation and training right?</p></li>
<li><p>how long do I train? say I use 1 fold (about 42 data sets per fold) and i reach my desired error threshold. Do I stop? and use the test data? else I load up the next set and keep training? what if I run out of data set before I reach my desired error threshold?</p></li>
<li><p>also should I follow something like this? </p>

<ol>
<li>use input values</li>
<li>feed forward, then compare error</li>
<li>backpropagate and adjust weights</li>
<li>repeat process a-c until i reach error threshold and finish all data in the current fold?</li>
</ol></li>
</ol>

<p>thank you for your time and response. I am really trying to understand how to use the dataset. I will update you guys once I have written the code.</p>