Classification trees are widely used in the machine learning and data mining communities for modeling propositional data. Recent work has extended this basic paradigm to probabili...
Jennifer Neville, David Jensen, Lisa Friedland, Mi...
In this paper we prove that the well-known correspondence between the forward-backward algorithm for hidden Markov models (HMMs) and belief propagation (BP) applied to HMMs can be...
In this paper, an efficient method for language model lookahead probability generation is presented. Traditional methods generate language model look-ahead (LMLA) probabilities fo...
A relational probability tree (RPT) is a type of decision tree that can be used for probabilistic classification of instances with a relational structure. Each leaf of an RPT cont...
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...