Titlebook: Inductive Logic Programming; 9th International Wo Sašo Džeroski,Peter Flach Conference proceedings 1999 Springer-Verlag Berlin Heidelberg 1

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Some Elements of Machine Learningch systems have been predictive accuracy and interpretability. Although . have shown that accuracy alone is a poor metric for comparing learning systems, it is still important in most real-world applications. The quest for intelligibility, stressed from earliest days by Michie, Michalski and others,

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Refinement Operators Can Be (Weakly) Perfectct to syntactical restrictions in the form of input/output variable declarations (like in Progol). Since unfortunately no such optimal refinement operators exist, we settle for a weaker form of optimality and introduce an associated weaker form of subsumption which exactly captures a first incomplet

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Morphosyntactic Tagging of Slovene Using Progolibutes such as gender and case. In the case of Slovene there are 2,083 possible MSDs. P-Progol was used to learn morphosyntactic disambiguation rules from annotated data (consisting of 161,314 examples) produced by the MULTEXT-East project. P-Progol produced 1,148 rules taking 36 hours. Using simple

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1BC: A First-Order Bayesian Classifiertructural predicates referring to subterms (e.g. atoms from molecules), and properties applying to one or several of these subterms (e.g. a bond between two atoms). We describe an individual in terms of elementary features consisting of zero or more structural predicates and one property; these feat