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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/11382

Title: Comparing the Performance of Zero Mean Classification Functions under Unequal Misclassification Cost
Authors: Asamoah-Boaheng, Michael
Adebanji, Atinuke
Ababio, Nkansah
Keywords: Classification rules
Error rates
Discrimination functions
Minimum expected cost of misclassification
Issue Date: 2014
Publisher: American Journal of Applied Mathematics and Statistics
Citation: 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, vol. 2, no. 6 (2014): 409-415. doi: 10.12691/ajams-2-6-9.
Abstract: 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.
Description: An article published by American Journal of Applied Mathematics and Statistics, 2014, Vol. 2, No. 6, 409-415; Available online at http://pubs.sciepub.com/ajams/2/6/9
URI: http://hdl.handle.net/123456789/11382
Appears in Collections:College of Science

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