Titlebook: Machine Learning: ECML-94; European Conference Francesco Bergadano,Luc Raedt Conference proceedings 1994 Springer-Verlag Berlin Heidelberg

Needlework

genesis

Bottom-up induction of oblivious read-once decision graphs,ing these structures from labelled instances. The algorithm is robust with respect to irrelevant attributes, and experimental results show that it performs well on problems considered difficult for symbolic induction methods, such as the Monk‘s problems and parity.

BORE

Contort

BMWk revisited generalization and formalization of an algorithm for detecting recursive relations ipaper presents a formalization and a generalization of the BMWk methodology, which stems from program synthesis from examples, ten years ago. The framework of the proposed formalization is term rewriting. It allows to state some theoretical results on the qualities and limitations of the method.

玉米棒子

有限

Sample PAC-learnability in model inference,It is argued that uniform sample PAC-learnability cannot be expected with most of the ‘interesting’ model classes. Polynomial sample learnability can only be accomplished in classes of programs having a fixed maximum number of clauses. We have proved that the class of context free programs in a fixe

abysmal

Controlling constructive induction in CIPF: An MDL approach,nt. It is described in terms of a . for constructive induction. We focus on the problem of controlling the abundance of opportunities for constructively adding new attributes. In C.PF the so-called . (MDL) principle acts as a powerful control heuristic. This is also confirmed in the experiments repo

受人支配

Using constraints to building version spaces,ve examples are represented as constraints on the search space. This representation allows for defining a partial order on the negative examples and on attributes too. It is shown that only minimal negative examples and minimal attributes are to be considered when building the set G. These results h

拱形面包

On the utility of predicate invention in inductive logic programming,cient for the learning task. However, whether predicate invention really helps to make learning succeed in the extended language depends on the bias that is currently employed..In this paper we investigate for which commonly employed language biases predicate invention is an appropriate shift operat

Chronic

Learning problem-solving concepts by reflecting on problem solving,, and learning enables improved problem-solving performance. Different models of problem solving, however, recognize different knowledge needs, and, as a result, set up different learning tasks. Some recent models analyze problem solving in terms of generic tasks, methods, and subtasks. These models