Please use this identifier to cite or link to this item: https://hdl.handle.net/10216/67386
Author(s): Alexessander Alves
Rui Camacho
Eugénio Oliveira
Title: Discovery of functional relationships in multi-relational data using inductive logic programming
Issue Date: 2004
Abstract: ILP systems have been largely applied to datamining classification tasks with a considerable success. The use of ILP systems in regression tasks has been far less successful. Current systems have very limited numerical reasoning capabilities, which limits the application of ILP to discovery of functional relationships of numeric nature. This paper proposes improvements in numerical reasoning capabilities of ILP systems for dealing with regression tasks. 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 PAC method to evaluate learning performance. We have found these extensions essential to improve on results over machine learning and statistical-based algorithms used in the empirical evaluation study.
Subject: Programação, Ciências da computação e da informação
Programming, 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/10216/67386
Source: FOURTH IEEE INTERNATIONAL CONFERENCE ON DATA MINING, PROCEEDINGS
Document Type: Artigo em Livro de Atas de Conferência Internacional
Rights: restrictedAccess
License: https://creativecommons.org/licenses/by-nc/4.0/
Appears in Collections:FEUP - Artigo em Livro de Atas de Conferência Internacional

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