A first-order framework for top-down induction of logical decision trees is introduced. The expressivity of these trees is shown to be larger than that of the flat logic programs which are typically induced by classical ILP systems, and equal to that of first-order decision lists. These results are related to predicate invention and mixed variable quantification. Finally, an implementation of this framework, the TILDE system, is presented and empirically evaluated. (C) 1998 Elsevier Science B.V. All rights reserved.status: publishe
We present one way of combining a logical framework and first-order logic. The logical framework is ...
Rad ne sadrži sažetak.This paper examines the use of truth tree method in the context of proposition...
We present one way of combining a logical framework and first-order logic. The logical framework is ...
We study and implement algorithms to revise and learn first-order logical theories, written in claus...
An alternating decision tree is a model that generalizes decision trees and boosted decision trees. ...
Abstract. We present BUFOIDL, a new bottom-up algorithm for learning first order decision lists. Alt...
We present an extension of Binary Decision Diagrams (BDDs) such that they can be used for predicate ...
AbstractBinary decision diagrams (BDDs) are known to be a very efficient technique to handle proposi...
This paper presents a method for inducing logic programs from examples that learns a new class of co...
Binary decision diagrams (BDDs) are known to be a very efficient technique to handle propositional f...
This paper describes the design and analysis of a system developed to learn comprehensible theories...
In best-first top-down induction of decision trees, the best split is added in each step (e.g. the s...
This paper presents a method for inducing logic programs from examples that learns a new class of co...
These lecture notes are intended to introduce the reader to the basic notions of the first order pr...
This paper deals with learning first-order logic rules from data lacking an explicit classification ...
We present one way of combining a logical framework and first-order logic. The logical framework is ...
Rad ne sadrži sažetak.This paper examines the use of truth tree method in the context of proposition...
We present one way of combining a logical framework and first-order logic. The logical framework is ...
We study and implement algorithms to revise and learn first-order logical theories, written in claus...
An alternating decision tree is a model that generalizes decision trees and boosted decision trees. ...
Abstract. We present BUFOIDL, a new bottom-up algorithm for learning first order decision lists. Alt...
We present an extension of Binary Decision Diagrams (BDDs) such that they can be used for predicate ...
AbstractBinary decision diagrams (BDDs) are known to be a very efficient technique to handle proposi...
This paper presents a method for inducing logic programs from examples that learns a new class of co...
Binary decision diagrams (BDDs) are known to be a very efficient technique to handle propositional f...
This paper describes the design and analysis of a system developed to learn comprehensible theories...
In best-first top-down induction of decision trees, the best split is added in each step (e.g. the s...
This paper presents a method for inducing logic programs from examples that learns a new class of co...
These lecture notes are intended to introduce the reader to the basic notions of the first order pr...
This paper deals with learning first-order logic rules from data lacking an explicit classification ...
We present one way of combining a logical framework and first-order logic. The logical framework is ...
Rad ne sadrži sažetak.This paper examines the use of truth tree method in the context of proposition...
We present one way of combining a logical framework and first-order logic. The logical framework is ...