Simple implementation of the "hashing trick" for featurization

This produces fixed-size feature vectors given any number of key/value pairs, for any value type V:Group and key type that can be converted to a byte array. This is most directly inspired by Jeremy Hoon's recent post on [hash kernels](http://jeremydhoon.github.com/2013/03/19/abusing-hash-kernels-for-wildly-unprincipled-machine-learning/), but is better know from its use in Vowpal Wabbit etc - see http://en.wikipedia.org/wiki/Feature_hashing