  Multivariate Analysis is an increasingly common tool in experimental high
energy physics; however, many of the common approaches were borrowed from other
fields. We clarify what the goal of a multivariate algorithm should be for the
search for a new particle and compare different approaches. We also translate
the Neyman-Pearson theory into the language of statistical learning theory.
