Titlebook: Machine Learning: ECML-95; 8th European Confere Nada Lavrac,Stefan Wrobel Conference proceedings 1995 Springer-Verlag Berlin Heidelberg 199

Aromatic

Learning abstract planning cases,om given concrete cases. For this purpose, we have developed a new abstraction methodology that allows to completely . of a planning case, when the concrete and abstract languages are given by the user. Furthermore, we present a learning algorithm which is correct and complete with respect to the in

CRAB

The role of prototypicality in exemplar-based learning,perties approach, and a similarity-based approach, and suggests measures that implement the different approaches. The proposed measures are tested in a set of experiments. The results of the experiments show that prototypicality serves as a good storing filter in storage reduction algorithms; combin

Friction

Specialization of recursive predicates,sible to specialize or remove any of the clauses in a refutation of a negative example without excluding any positive examples. A previously proposed solution to this problem is to apply program transformation in order to obtain non-recursive target predicates from recursive ones. However, the appli

BROTH

暴露他抗議

commute

QUAIL

不可磨滅

comely

The power of decision tables,spaces possible, and usually they are easy to understand. Experimental results show that on artificial and real-world domains containing only discrete features, IDTM, an algorithm inducing decision tables, can sometimes outperform state-of-the-art algorithms such as C4.5. Surprisingly, performance i

Prostatism

Pruning multivariate decision trees by hyperplane merging,y contain binary tests questioning to what side of a hyperplane the example lies. Most of these algorithms use . mechanisms similar to those of traditional decision trees. Nearly unexplored remains the large domain of . methods, where a new decision test (derived from previous decision tests) replac