Feature selection should not be part of SupervisedClassifier

[Peter]

needs #108 #109 #110 #111 #112 #113 #114 #115 #116 #120 #122

The simple reason is think modules. The longer reason is that present design is not general enough. I have the following user case:

I wanna build an ensemble of classifiers to cross-validate the perfromance. In this procedure, I wanna select feature using a ranked list (InputRanker?), though I do not want to select the top features in the ranked list, but rather say features in position 151-251.

There is no way I can do that as it is now. The feature selection in SupervisedClassifier? could of course be extended, but I think it would become to complex and it is better to lift out the whole thing to a new class. Polymorphism could be really useful here, besides having the obvious class be constructed from a Score, start feature and end feature, one could imagine having a class constructed from a vector of indices. I suppose a sensible interface would be to only have one function get(const DataLookup2D& entire_data, DataLookup2D& selected data). Other variables needed are set in corrsponding constructor.