The class FKFeatures implements Fischer kernel features obtained from
two Hidden Markov models.

It was used in

K. Tsuda, M. Kawanabe, G. Raetsch, S. Sonnenburg, and K.R. Mueller. A new
discriminative kernel from probabilistic models. Neural Computation,
14:2397-2414, 2002.

which also has the details.

Note that FK-features are computed on the fly, so to be effective feature
caching should be enabled.

It inherits its functionality from CSimpleFeatures, which should be
consulted for further reference.

