This site has been permanently archived. This is a static copy provided by the University of Southampton.

TY - GEN ID - cogprints8084 UR - http://cogprints.org/8084/ A1 - Scheler, Gabriele Y1 - 1994/// N2 - 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. PB - Springer KW - phonetic features KW - distance metrics KW - outliers KW - classification TI - Feature Selection with Exception Handling - An Example from Phonology AV - public ER -