Ensemble Validation: Selectivity has a Price, but Variety is Free

10/04/2016
by   Eric Bax, et al.
0

If classifiers are selected from a hypothesis class to form an ensemble, bounds on average error rate over the selected classifiers include a component for selectivity, which grows as the fraction of hypothesis classifiers selected for the ensemble shrinks, and a component for variety, which grows with the size of the hypothesis class or in-sample data set. We show that the component for selectivity asymptotically dominates the component for variety, meaning that variety is essentially free.

READ FULL TEXT

Please sign up or login with your details

Forgot password? Click here to reset