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AAAI
2004
13 years 8 months ago
On the Optimality of Probability Estimation by Random Decision Trees
Random decision tree is an ensemble of decision trees. The feature at any node of a tree in the ensemble is chosen randomly from remaining features. A chosen discrete feature on a...
Wei Fan
ICDM
2005
IEEE
143views Data Mining» more  ICDM 2005»
14 years 18 days ago
Effective Estimation of Posterior Probabilities: Explaining the Accuracy of Randomized Decision Tree Approaches
There has been increasing number of independently proposed randomization methods in different stages of decision tree construction to build multiple trees. Randomized decision tre...
Wei Fan, Ed Greengrass, Joe McCloskey, Philip S. Y...
FCS
2006
13 years 8 months ago
Principles of Optimal Probabilistic Decision Tree Construction
Probabilistic (or randomized) decision trees can be used to compute Boolean functions. We consider two types of probabilistic decision trees - one has a certain probability to give...
Laura Mancinska, Maris Ozols, Ilze Dzelme-Berzina,...
ICML
2001
IEEE
14 years 7 months ago
Obtaining calibrated probability estimates from decision trees and naive Bayesian classifiers
Accurate, well-calibrated estimates of class membership probabilities are needed in many supervised learning applications, in particular when a cost-sensitive decision must be mad...
Bianca Zadrozny, Charles Elkan
DAGM
2001
Springer
13 years 11 months ago
Optimal Camera Parameter Selection for State Estimation with Applications in Object Recognition
In this paper we introduce a formalism for optimal camera parameter selection for iterative state estimation. We consider a framework based on Shannon’s information theory and se...
Joachim Denzler, Christopher M. Brown, Heinrich Ni...