Lazy Learning: A Logical Method for Supervised Learning
Gianluca Bontempi, Mauro Birattari, Hugues Bersini · Studies in fuzziness and soft computing · 2002
The traditional approach to supervised learning is global modeling which describes the relationship between the input and the output with an analytical function over the whole input domain. What makes global modeling appealing is the nice property that even for huge datasets, a parametric model can be stored in a small memory. Also, the evaluation of the parametric model requires a short program that can be executed in a reduced amount of time. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.