In mathematics the signal-to-noise statistic distance between two vectors a and b with mean values
respectively is: In the case of Gaussian-distributed data and unbiased class distributions, this statistic can be related to classification accuracy given an ideal linear discrimination, and a decision boundary can be derived.
[1] This distance is frequently used to identify vectors that have significant difference.
One usage is in bioinformatics to locate genes that are differential expressed on microarray experiments.
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