Performance of several class prior change models was studied across 4
data sets.
Usage
data(prior)
Arguments
Format
List of 2 data.frames: accuracy contains the mean and standard error of
the performance measures (sqErr and accuracy), data.set.info contains
meta-data about the dimension and number of positive and negative
examples in each data set.
References
du Plessis MC, Sugiyama M.
Semi-Supervised Learning of Class Balance under Class-Prior Change by
Distribution Matching. ICML 2012.