The ROSETTA C++ library is a collection of C++ classes and routines that enable discernibility-based empirical modelling and data mining, developed as part of my dissertation. A brief presentation of the library can be found therein.
Locally weighted polynomial regression LWPR is a popular instance based al gorithm for learning continuous non linear mappings For more than two or three in puts and for more than a few thousand dat apoints the computational expense of pre dictions is daunting We discuss drawbacks with previous approaches to dealing with this problem
