Javadoc
Evaluator that implements the concept of LocallyWeightedLearning. That
is, given an input point, this function re-weights the dataset according
to how "close" the dataset inputs are to the given input. An inner-loop
learner then uses the re-weighted to compute a local function
approximator for this input. The output of this class is the output
of the local function approximator, which is recomputed each time
evaluate() is called. Thus, evaluate() on this method is relatively
expensive (because it calls learn() on the given BatchLearner)