Using an Artificial Neural Network to Classify Multi-component Emission
  Line Fits
  We present The Machine, an artificial neural network (ANN) capable of
differentiating between the numbers of Gaussian components needed to describe
the emission lines of Integral Field Spectroscopic (IFS) observations. Here we
show the preliminary results of the S7 first data release (Siding Spring
Southern Seyfert Spectro- scopic Snapshot Survey, Dopita et al. 2015) and SAMI
Galaxy Survey (Sydney-AAO Multi-object Integral Field Unit, Croom et al. 2012)
to classify whether the emission lines in each spatial pixel are composed of 1,
2, or 3 different Gaussian components. Previously this classification has been
done by individual people, taking an hour per galaxy. This time investment is
no longer feasible with the large spectroscopic surveys coming online.
