r-cran-unbalanced - 2.0-2 main

A dataset is said to be unbalanced when the class of interest (minority
class) is much rarer than normal behaviour (majority class). The cost of
missing a minority class is typically much higher that missing a
majority class. Most learning systems are not prepared to cope with
unbalanced data and several techniques have been proposed. This package
implements some of most well-known techniques and propose a racing
algorithm to select adaptively the most appropriate strategy for a given
unbalanced task.