Discovery of functional relationships in multi-relational data using inductive logic programming

• Type: Article in International Conference Proceedings Book
• Date: 2004

Authors

Alexessander Alves (Author) Other; Rui Camacho (Author) FEUP; Eugénio Oliveira (Author) FEUP

Conference proceedings International

Title: FOURTH IEEE INTERNATIONAL CONFERENCE ON DATA MINING, PROCEEDINGS

Pages: 319-322

4th IEEE International Conference on Data Mining

Brighton, ENGLAND, NOV 01-04, 2004

Indexing

ISI Proceedings

ISI Web of Knowledge - 1 Citation

Scopus - 1 Citation

INSPEC

Scientific classification

FOS: Natural sciences > Computer and information sciences

CORDIS: Physical sciences > Computer science > Programming

Other information

Authenticus ID: P-000-CRN

DOI: 10.1109/icdm.2004.10053

Abstract (EN): 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 4