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» Learning with Mixtures of Trees
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UAI
2003
13 years 9 months ago
Bayesian Hierarchical Mixtures of Experts
The Hierarchical Mixture of Experts (HME) is a well-known tree-structured model for regression and classification, based on soft probabilistic splits of the input space. In its o...
Christopher M. Bishop, Markus Svensén
IJAR
2006
98views more  IJAR 2006»
13 years 7 months ago
Inference in hybrid Bayesian networks with mixtures of truncated exponentials
Mixtures of truncated exponentials (MTE) potentials are an alternative to discretization for solving hybrid Bayesian networks. Any probability density function can be approximated...
Barry R. Cobb, Prakash P. Shenoy
KDD
2004
ACM
237views Data Mining» more  KDD 2004»
14 years 8 months ago
Bayesian Model-Averaging in Unsupervised Learning From Microarray Data
Unsupervised identification of patterns in microarray data has been a productive approach to uncovering relationships between genes and the biological process in which they are in...
Mario Medvedovic, Junhai Guo
IJCAI
1989
13 years 9 months ago
Generating Better Decision Trees
A new decision tree learning algorithm called IDX is described. More general than existing algorithms, IDX addresses issues of decision tree quality largely overlooked in the arti...
Steven W. Norton
ICPR
2004
IEEE
14 years 9 months ago
Learning Spatial Context from Tracking using Penalised Likelihoods
MAP estimation of Gaussian mixtures through maximisation of penalised likelihoods was used to learn models of spatial context. This enabled prior beliefs about the scale, orientat...
Hammadi Nait-Charif, Stephen J. McKenna