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Article

RULES3-EXT Improvements on RULES-3 Induction Algorithm

by
Hassan I. Mathkour
College of Computer and Information Sciences Department of Computer Science, King Saud University, Riyadh, 11653, Saudi Arabia
Math. Comput. Appl. 2010, 15(3), 318-324; https://doi.org/10.3390/mca15030318
Published: 1 December 2010
Versions Notes

Abstract

This paper describes RULES3-EXT, a new algorithm for inductive learning. It has been developed to cope with some drawbacks of RULES-3 induction algorithm. The extra features of RULES3-EXT are (1) The number of required files to extract a knowledge base (a set of rules) is reduced to 2 from 3 (2) The repeated examples are eliminated, (3) The users are able to change the order of attributes and (4) The system is able to fire rule(s) partially if any of the extracted rules cannot fully be satisfied by an unseen example. The new algorithm has been tested on well known data sets and the efficiency found to be superior to that of RULES-3.
Keywords: Inductive Learning; Induction; Knowledge Acquisition; Machine Learning Inductive Learning; Induction; Knowledge Acquisition; Machine Learning

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MDPI and ACS Style

Mathkour, H.I. RULES3-EXT Improvements on RULES-3 Induction Algorithm. Math. Comput. Appl. 2010, 15, 318-324. https://doi.org/10.3390/mca15030318

AMA Style

Mathkour HI. RULES3-EXT Improvements on RULES-3 Induction Algorithm. Mathematical and Computational Applications. 2010; 15(3):318-324. https://doi.org/10.3390/mca15030318

Chicago/Turabian Style

Mathkour, Hassan I. 2010. "RULES3-EXT Improvements on RULES-3 Induction Algorithm" Mathematical and Computational Applications 15, no. 3: 318-324. https://doi.org/10.3390/mca15030318

APA Style

Mathkour, H. I. (2010). RULES3-EXT Improvements on RULES-3 Induction Algorithm. Mathematical and Computational Applications, 15(3), 318-324. https://doi.org/10.3390/mca15030318

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