Utilize este identificador para referenciar este registo:
https://hdl.handle.net/10216/67386
Autor(es): | Alexessander Alves Rui Camacho Eugénio Oliveira |
Título: | Discovery of functional relationships in multi-relational data using inductive logic programming |
Data de publicação: | 2004 |
Resumo: | 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. |
Assunto: | Programação, Ciências da computação e da informação Programming, Computer and information sciences |
Áreas do conhecimento: | Ciências exactas e naturais::Ciências da computação e da informação Natural sciences::Computer and information sciences |
URI: | https://hdl.handle.net/10216/67386 |
Fonte: | FOURTH IEEE INTERNATIONAL CONFERENCE ON DATA MINING, PROCEEDINGS |
Tipo de Documento: | Artigo em Livro de Atas de Conferência Internacional |
Condições de Acesso: | restrictedAccess |
Licença: | https://creativecommons.org/licenses/by-nc/4.0/ |
Aparece nas coleções: | FEUP - Artigo em Livro de Atas de Conferência Internacional |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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52628.pdf Restricted Access | 158.22 kB | Adobe PDF | Request a copy from the Author(s) |
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