A page from the OpenDepot.org service

Jump to the start of the main contents

Abldin, B. and Dom, R. M. and Zain, R. B. 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 0031-3025

[img] PDF
Download (107Kb)


    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.

    Item Type: Article
    Uncontrolled Keywords: Fuzzy concept
    Subjects: Medicine and Dentistry
    Divisions: UNSPECIFIED
    Depositing User: Prof. Dr. Rosnah Mohd Zain
    Date Deposited: 31 Jan 2012 03:44
    Last Modified: 10 Feb 2012 03:08
    URI: http://opendepot.org/id/eprint/592

    Actions (login required)

    View Item