Libagf is a machine learning library that includes adaptive kernel density estimators using Gaussian kernels and k-nearest neighbours. Operations include statistical classification, interpolation/non-linear regression and pdf estimation. For statistical classification there is a borders training feature for creating fast and general pre-trained models that nonetheless return the conditional probabilities. Libagf also includes clustering algorithms as well as comparison and validation...
That project aims at providing a clean API and a simple implementation, as a C++ library, of a Travel-oriented fare engine. It corresponds to the simulated version of the real-world Fare Quote System.