An adaptive fuzzy regression model for the prediction of dichotomous response variables

Zain, R.B. and Abldin, B. and Dom, R.M. and Kareem, S.A. (2007) An adaptive fuzzy regression model for the prediction of dichotomous response variables. ICCSA 2007: Proceedings of the Fifth International Conference on Computational Science and Applications. pp. 14-19. ISSN 978-0-7695-2945-5, DOI https://doi.org/10.1109/icsa.2007.37.

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Abstract

This paper proposes an adaptive technique in the prediction of dichotomous response variable by combining fuzzy concept with statistical logistic regression. The model was tested on an oral cancer dataset in predicting oral cancer susceptibility. In this paper we will present the development, evaluation and validation of the proposed model based on the experiment carried out. Explanatory power of the adaptive model was calculated and compared with fuzzy neural network and statistical logistic regression models using calibration and discrimination techniques. Area under ROC values calculated indicates that the proposed model has compatible predictive ability to both fuzzy neural network and statistical logistic regression models. © 2007 IEEE.

Item Type:	Article
Funders:	UNSPECIFIED
Uncontrolled Keywords:	Fuzzy concept
Subjects:	Q Science > QA Mathematics Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > TA Engineering (General). Civil engineering (General)
Divisions:	Faculty of Dentistry > Dept of Oral Pathology & Oral Medicine & Periodontology
Depositing User:	Prof. Dr. Rosnah Mohd Zain
Date Deposited:	06 Jan 2012 01:18
Last Modified:	27 Oct 2014 06:13
URI:	http://eprints.um.edu.my/id/eprint/2356

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