LEARNER CREATION

The implementor of a learning algorithm will
deliver their software by means of a

   learner *mk_xxx_learner()

function.  See examples/linearreg.cpp for an
example of this and of the general process of
implementing the functions for a new learner.
When creating a learner in mk_xxx_learner,
the implementor should set the fields to
reflect all the functions they have provided.
Fields representing any unimplemented
functions should be NULL.

Remember that the xxx_predict function MUST
be implemented for all learners.

If the learner uses training, then
mk_xxx_hypo and free_xxx_hypo must be
provided.

If the learners uses parameters, then
mk_xxx_default_params and free_xxx_params
must be provided.

Having written mk_xxx_learner and the
functions for that learner, the implementor
of a new algorithm has two more things to do.
They must modify the definitions of the
following two functions given in the file
examples/learner.cpp, to add in their new
learner.     

learner *mk_learner_from_string(char *learner_name)
string_array *mk_learner_names() 

The string used to name the learner must be
identical in both cases.