dai-ensembleparameter-2003.pdf (171.22 kB)
Ensemble parameter estimation for graphical models
conference contributionposted on 2003-01-01, 00:00 authored by Yiqing Tu, Gang LiGang Li, Honghua Dai
Parameter Estimation is one of the key issues involved in the discovery of graphical models from data. Current state of the art methods have demonstrated their abilities in different kind of graphical models. In this paper, we introduce ensemble learning into the process of parameter estimation, and examine ensemble parameter estimation methods for different kind of graphical models under complete data set and incomplete data set. We provide experimental results which show that ensemble method can achieve an improved result over the base parameter estimation method in terms of accuracy. In addition, the method is amenable to parallel or distributed processing, which is an important characteristic for data mining in large data sets.