title: Regression or Classification?
body: <p>When using a neural network to predict the error percentage of a manufacturing process, where there are some inputs into the process out of our control (random) is it best to use regression or classification?</p>
  
  <p>Example,</p>
  
  <p>An output can be error rates ranging from -900% to +900% with the average &amp; median error being 9% (Its a fat tailed bell curve). Should we use regression and attempt to predict the error amount or classify errors into sigmas from the median, for example 900% is 5 Sigmas from the median. We would therefore have 11 categories -5 to +5 </p>