ON ASSESSING EFFICIENCY OF AN ALTERNATIVE CLASSIFIER THROUGH SENSITIVITY AND SPECIFICITY
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Date
2017-05-01
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Publisher
International Centre for Advance Studies
Abstract
We examine the efficiency of a competing classifier through sensitivity and specificity, utilizing a Monte Carlo Study.We observed that when sensitivity or specificity or both are low, the efficiency of such classifier is poor and not desirable. We found that even with large sample size empirical efficiency does not show any appreciable difference. Our results suggest that estimation of efficiency is not good when we have small sample sizes (< 30 ). We found that if the sensitivity or specificity or both are high (> 0.75 ), such classifier have good efficiency. This is slightly more relaxed than the results by other researchers where sensitivity and specificity of .80 or higher was recommended.
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Keywords
Sensitivity, Specificity, Efficiency, Competing Classifier, Screening Test