Ensemble Learning

In Advances in Independent Component Analysis, ed. Mark Girolami (Springer, 2000). In press.

Harri Lappalainen¹ - James W. Miskin²

¹Helsinki University of Technology, Neural Networks Research Centre, P.O. Box 5400, FIN-02015 HUT, Finland
²Cavendish Laboratory, Cambridge CB3 0HE, UK

Abstract:

This chapter gives a tutorial introduction to Ensemble Learning, a recently developed Bayesian method. For many problems it is intractable to perform inferences using the true posterior density over the unknown variables. Ensemble Learning allows the true posterior to be approximated by a simpler approximate distribution for which the required inferences are tractable.