Learning algorithms, normalizers (used in inference; see {@link LBJ2.learn.Normalizer}), testing metrics (used in cross validation; see {@link LBJ2.learn.TestingMetric}), and other utility classes can be found in this package.

Learning algorithms are always associated with an evaluation algorithm that actually does the classifying; the learning algorithm simply sets the parameters of that classifying function. Thus, they are implemented here as {@link LBJ2.classify.Classifier}s that can change their representations (i.e., their parameters) given training data. @author Nick Rizzolo