MOD: modified the calculation of jacobian and added new functionality to NeuralNetwork class to support the new jacobian calculation

ADD: added kallman filter learning method (not tested) and random learning method + modifications in neural network to support the new functionality

ADD+MOD+FIX: added new evaluation functions for debug/testing purposes, modified random generation of parameters, fixed the calculation of gradient via backpropagation

ENH: Now it's possible to specify different neuron types for different hidden layers in FullyConnectedFFNs.

ENH: Methods print_* changed for overloaded methods write_*, which make possible writing not only to STDOUT, but also to the file.

ENH + NEW: Implemented the data normalization funcionality to DataSet. Created a new class NormalizationStrategy.

ENH: Only classes belonging to API are now contained in 4neuro.h. All those classes were enclosed in 'lib4neuro' namespace.

ADD: added preliminary version of gradient calculation vie backpropagation, added supporting methods to error classes and learning algorithms utilizing gradient calculation

ENH: Removed both linking and include dependencies from examples => lib4neuro can be used just by linking it and including its header without any external dependencies needed.

FIX: Fixed Boost include dependencies, so the examples don't have to be compiled with Boost include directory.