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A Bayesian approach for comparing cross-validated algorithms on multiple data sets.
The package allows to compare two algorithms whose performance has been assessed via cross-validation on multiple data sets. It performs a Bayesian correlated t-test on each data set and then merges their results via a Poisson-binomial inference. It returns the posterior probability of one algorithm having a higher mean score than the other on the provided collection of data sets. It accounts for the uncertainty and the correlation which characterize the cross-validation samples generated on each data set.

See also A Bayesian approach for comparing cross-validated algorithms on multiple data sets.

Information
Files BACC
Version1
Date1 January 2015
RequirementsR or Matlab

Authors

Giorgio Corani, PhD
Senior Researcher
 
Alessio Benavoli, PhD
Professor