From the site:
This page documents all the machine learning algorithms present in the library. In particular, there are algorithms for performing classification, regression, clustering, anomaly detection, and feature ranking, as well as algorithms for doing more specialized computations.
A good tutorial and introduction to the general concepts used by most of the objects in this part of the library can be found in the svm example program. After reading this example another good one to consult would be the model selection example program. Finally, if you came here looking for a binary classification or regression tool then I would try the krr_trainer first as it is generally the easiest method to use.
The major design goal of this portion of the library is to provide a highly modular and simple architecture for dealing with kernel algorithms….
Update: Dlib – machine learning. Why I left out the library name I cannot say. Sorry!