public class SignalNoiseRatio
The signal-to-noise (S2N) metric ratio is a univariate feature ranking metric,
which can be used as a feature selection criterion for binary classification
problems. S2N is defined as |μ1 - μ2| / (σ1 + σ2),
where μ1 and μ2 are the mean value of the variable
in classes 1 and 2, respectively, and σ1 and σ2
are the standard deviations of the variable in classes 1 and 2, respectively.
Clearly, features with larger S2N ratios are better for classification.
M. Shipp, et al. Diffuse large B-cell lymphoma outcome prediction by gene-expression profiling and supervised machine learning. Nature Medicine, 2002.