Please use this identifier to cite or link to this item: https://hdl.handle.net/10216/67382
Author(s): Alexessander Alves
Rui Camacho
Eugénio Oliveira
Title: Improving numerical reasoning capabilities of inductive logic programming systems
Issue Date: 2004
Abstract: Inductive Logic Programming (ILP) systems have been largely applied to classification problems with a considerable success. The use of ILP systems in problems requiring numerical reasoning capabilities has been far less successful. Current systems have very limited numerical reasoning capabilities, which limits the range of domains where the ILP paradigm may be applied. This paper proposes improvements in numerical reasoning capabilities of ILP systems. It proposes the use of statistical-based techniques like Model Validation and Model Selection to improve noise handling and it introduces a new search stopping criterium based on the PAG method to evaluate learning performance. We have found these extensions essential to improve on results mer statistical-based algorithms for time series forecasting used in the empirical evaluation study.
Subject: Ciências da computação e da informação
Computer and information sciences
Scientific areas: Ciências exactas e naturais::Ciências da computação e da informação
Natural sciences::Computer and information sciences
URI: https://repositorio-aberto.up.pt/handle/10216/67382
Source: ADVANCES IN ARTIFICIAL INTELLIGENCE - IBERAMIA 2004
Document Type: Artigo em Revista Científica Internacional
Rights: openAccess
License: https://creativecommons.org/licenses/by-nc/4.0/
Appears in Collections:FEUP - Artigo em Revista Científica Internacional

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