Boosting grammatical inference with confidence oracles

In this paper we focus on the adaptation of boosting to grammatical inference. We aim at improving the performances of state merging algorithms in the presence of noisy data by using, in the update rule, additional information provided by an oracle. This strategy requires the construction of a new weighting scheme that takes into account the confidence in the labels of the examples. We prove that our new framework preserves the theoretical properties of boosting. Using the state merging algorithm rpni , we describe an experimental study on various datasets, showing a dramatic improvement of performances.

• Type: Conference
• Year: 2004
• Where: ICML
• Authors: Jean-Christophe Janodet, Richard Nock, Marc Sebban, Henri-Maxime Suchier
• Keywords: Grammatical Inference, ICML 2004, Machine Learning, State Merging Algorithm, State Merging Algorithms