American Journal of Applied Mathematics and Statistics
ISSN (Print): 2328-7306 ISSN (Online): 2328-7292 Website: Editor-in-chief: Mohamed Seddeek
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American Journal of Applied Mathematics and Statistics. 2014, 2(6), 409-415
DOI: 10.12691/ajams-2-6-9
Open AccessArticle

Comparing the Performance of Zero Mean Classification Functions under Unequal Misclassification Cost

Michael Asamoah-Boaheng1, , Atinuke O. Adebanji2 and Nkansah Ababio3

1School of Graduate Studies Research and Innovation, Kumasi Polytechnic, Box 854, Kumasi, Ghana

2Department of Mathematics, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

3Kofi Agyei Senior High School, P.O Box AN 2471 Ash-Town Kumasi, Bampenase-Ashanti

Pub. Date: December 19, 2014

Cite this paper:
Michael Asamoah-Boaheng, Atinuke O. Adebanji and Nkansah Ababio. Comparing the Performance of Zero Mean Classification Functions under Unequal Misclassification Cost. American Journal of Applied Mathematics and Statistics. 2014; 2(6):409-415. doi: 10.12691/ajams-2-6-9


In this study the performance of Minimum Expected Cost of Misclassification method (MECM) and Quadratic Discriminant Function approach (QDF) were compared and evaluated for the case of equal mean discrimination under unequal misclassification cost. 30 pairs of Female liked sex twins extracted from Stocks (1933) ten (10) variate data on 832 twin children was used for evaluation. Discriminant functions were derived under each of the following misclassification cost ratios; 1: 1, 1: 2, 1: 3 and 1: 4 and their error rate estimates determined using the Cross Validation (CV) and Balanced Error Rate (BER) methods. Least Mean error rates were recorded under QDF method as compared to that of MECM. The error rate estimates showed the QDF outperforming the MECM in the provision of maximum separation between the two groups. Also the two classification rules were found to be sensitive to misclassification cost ratios exceeding 1:2.

classification rules error rates discriminant functions minimum expected cost of misclassification

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