Discovering regression data quality through clustering methods
Dario Malchiodi, Simone Bassis, Lorenzo Valerio · Frontiers in artificial intelligence and applications · 2009
We propose the use of clustering methods in order to discover the quality of each element in a training set to be subsequently fed to a regression algorithm. The paper shows that these methods, used in combination with regression algorithms taking into account the additional information conveyed by this kind of quality, allow the attainment of higher performances than those obtained through standard techniques.