Inducing a classification function from a set of examples in the form of labeled instances is a standard problem in supervised machine learning. In this paper, we are concerned w...
We apply decision tree induction to the problem of discourse clue word sense disambiguation. The automatic partitioning of the training set which is intrinsic to decision tree ind...
It is well known that editing techniques can be applied to (large) sets of prototypes in order to bring the error rate of the Nearest Neighbour classifier close to the optimal Ba...
This paper develops the concept of usefulness in the context of supervised learning. We argue that usefulness can be used to improve the performance of classification rules (as me...
Gholamreza Nakhaeizadeh, Charles Taylor, Carsten L...
We report on a method for compiling decision trees into weighted finite-state transducers. The key assumptions are that the tree predictions specify how to rewrite symbols from an...