Recursive-rule extraction algorithm with J48graft and applications to generating credit scores

Hayashi, Yoichi (Department of Computer Science, Meiji University, Kawasaki, Japan) ; Tanaka, Yuki (Department of Computer Science, Meiji University, Kawasaki, Japan) ; Takagi, Tomohiro (Department of Computer Science, Meiji University, Kawasaki, Japan) ; Saito, Takamichi (Department of Computer Science, Meiji University, Kawasaki, Japan) ; Iiduka, Hideaki (Department of Computer Science, Meiji University, Kawasaki, Japan) ; Kikuchi, Hiroaki (Department of Frontier Media Science, Meiji University, Tokyo, Japan) ; Bologna, Guido (School of Engineering, Architecture and Landscape (hepia), HES-SO // University of Applied Sciences Western Switzerland) ; Mitra, Sushmita (Machine Intelligence Unit, Indian Statistical Institute, Kolkata, India)

The purpose of this study was to generate more concise rule extraction from the Recursive-Rule Extraction (Re-RX) algorithm by replacing the C4.5 program currently employed in Re-RX with the J48graft algorithm. Experiments were subsequently conducted to determine rules for six different two-class mixed datasets having discrete and continuous attributes and to compare the resulting accuracy, comprehensibility and conciseness. When working with the CARD1, CARD2, CARD3, German, Bene1 and Bene2 datasets, Re-RX with J48graft provided more concise rules than the original Re-RX algorithm. The use of Re-RX with J48graft resulted in 43.2%, 37% and 21% reductions in rules in the case of the German, Bene1 and Bene2 datasets compared to Re-RX. Furthermore, the Re-RX with J48graft showed 8.87% better accuracy than the Re-RX algorithm for the German dataset. These results confirm that the application of Re-RX in conjunction with J48graft has the capacity to facilitate migration from existing data systems toward new concise analytic systems and Big Data.


Keywords:
Article Type:
scientifique
Faculty:
Ingénierie et Architecture
School:
HEPIA - Genève
Institute:
inIT - Institut d'Ingénierie Informatique et des Télécommunications
Date:
2016-01
Pagination:
10 p.
Published in:
Journal of artificial intelligence and soft computing research
Numeration (vol. no.):
2016, vol. 6, no. 1, pp. 35-44
DOI:
ISSN:
2083-2567
Appears in Collection:



 Record created 2020-07-10, last modified 2020-07-14

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