Titlebook: Inductive Logic Programming; 7th International Wo Nada Lavrač,Sašo Džeroski Conference proceedings 1997 Springer-Verlag Berlin Heidelberg 1

步履蹒跚

MAOIS

On the complexity of some Inductive Logic Programming problems, and an integer . polynomial in ..∪.., does there exist a function-free Horn clause . with no more than . literais such that . subsumes each element in .. and . does not subsume any element in ... It is shown that this problem is .. complete. We derive some related results on the complexity of ILP a

antidote

搬运工

冰雹

Generating numerical literals during refinement,hoice of logic programs as the representation language. Our conjecture is that a generalisation of the representation language to Constraint Logic Programs provides an effective solution to this problem. We support this claim with the presentation of an algorithm called NUM, to which a top-down refi

Paraplegia

Lookahead and discretization in ILP,ad and Irani‘s text [9], but adapted and extended in such a way that it can cope with some aspects of discretization that only occur in relational learning problems (when indeterminate literals occur). The second technique is lookahead. It is a well-known problem in ILP that a learner cannot always

小卷发

Horizon

overrule

Maximum Entropy modeling with Clausal Constraints,d is a Bayesian method based on the principle that the target stochastic model should be as uniform as possible, subject to known constraints. . incorporates clausal constraints that are based on the evaluation of Prolog clauses in examples represented as Prolog programs. We build on an existing max

惊奇

Mining association rules in multiple relations, relation. We describe how this restriction can be overcome through the combination of the available algorithms with standard techniques from the field of inductive logic programming. We present the system ., which extends . [2] to mine association rules in multiple relations. We apply . to the natu