An instance-based approach to pattern association learning with application to the English past tense verb domain

We present a method for using instance-based learning to acquire Pattern As sociation (PA) rules and apply it to the English past tense verb domain. To retrieve exemplars, we introduce a distance metric for PA, Pattern Associa tion Metric for Exemplar-based Learning Algorithms (PAMELA), which extends that used in PEELS for classification. The associated pattern is then built by adapting that of the retrieved exemplar(s). We show that our algorithm IBPA-3, which uses exemplar distance weighting and attribute weighting, imp roves upon the C4.5-based SPA algorithm and, when tested on the difficult c ase of irregular verbs, out-performs the current state of the art algorithm for this problem, the relational learner, FOIDL. (C) 2001 Elsevier Science B.V. All rights reserved.