title: Feature Selection with Exception Handling - An Example from Phonology creator: Scheler, Gabriele subject: Machine Learning subject: Speech subject: Statistical Models subject: Phonology description: The goal in this paper is to show how the classification of phonetic features to phonemes can be acquired. This classificational process is modeled by a supervised feature selection method, based on adaptive distance measures. Exception handling is incorporated into a learned distance function by pointwise additions of Boolean functions for individual pattern combinations. An important result is the differentiation of rules and exceptions during learning. publisher: Springer contributor: Trappl, Robert date: 1994 type: Conference Paper type: PeerReviewed format: application/postscript identifier: http://cogprints.org/8084/2/scheler_phonology.ps format: application/pdf identifier: http://cogprints.org/8084/3/scheler_phonology.pdf identifier: Scheler, Gabriele (1994) Feature Selection with Exception Handling - An Example from Phonology. [Conference Paper] relation: http://cogprints.org/8084/