Abstract. Approaches to data mining proposed so far are mainly symbolic decision trees and numerical feedforward neural networks methods. While decision trees give, in many cases, ...
We consider three natural models of random logarithmic depth decision trees over Boolean variables. We give an efficient algorithm that for each of these models learns all but an ...
This article describes a new system for induction of oblique decision trees. This system, OC1, combines deterministic hill-climbing with two forms of randomization to nd a good ob...
We define a set of deterministic bottom-up left to right parsers which analyze a subset of Tree Adjoining Languages. The LR parsing strategy for Context Free Grammars is extended ...
In regular inference, the problem is to infer a regular language, typically represented by a deterministic finite automaton (DFA) from answers to a finite set of membership querie...