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Output details

11 - Computer Science and Informatics

Manchester Metropolitan University

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Output 23 of 37 in the submission
Article title

Inducing fuzzy regression tree forests using artificial immune systems

Type
D - Journal article
Title of journal
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Article number
-
Volume number
20
Issue number
supp02
First page of article
133
ISSN of journal
1793-6411
Year of publication
2012
URL
-
Number of additional authors
2
Additional information

<22>Presents a new method for inducing fuzzy decision forests from non-fuzzified data using an adapted artificial immune network. Core work from Ph.D. thesis of Gasir (successfully defended June-2012). Novelty lies in predicting a continuous output value through the combination of optimised fuzzy forests from real-world data. Strength of the method is that data does not require fuzzification before forest induction, thus reducing pre-processing time and need for subjective human experts. Extensive experimental results are presented using established datasets in the field.

Interdisciplinary
-
Cross-referral requested
-
Research group
B - Computational Intelligence and Reasoning
Citation count
0
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-