Area Under the Binormal ROC Curve Using Confidence Intervals
On the Comparison of AUC of the Binormal ROC Curves Using Confidence Intervals A Study
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The immense importance of classification problems have been extensively increasing day by day in several areas viz., engineering, medical, biological sciences, radiology, epidemiology etc. Owing such significance, Receiver Operating Characteristic (ROC) curve analysis plays a vital role as a classifier performance assist tool in medicine or health related areas. ROC curve is a graphical representation of sensitivity and (1-specificity) on XY plane. In many diagnostic problems one needs to assess the performance of a classifier or more than one classifier, roc curve analysis accomplish all requ...
The immense importance of classification problems have been extensively increasing day by day in several areas viz., engineering, medical, biological sciences, radiology, epidemiology etc. Owing such significance, Receiver Operating Characteristic (ROC) curve analysis plays a vital role as a classifier performance assist tool in medicine or health related areas. ROC curve is a graphical representation of sensitivity and (1-specificity) on XY plane. In many diagnostic problems one needs to assess the performance of a classifier or more than one classifier, roc curve analysis accomplish all requirements as one of the best statistical tool. The present study emphasis on the comparison of area under the binormal roc curve using confidence intervals for location and scale parameters.This book briefly explains regarding some statistical pakages like MS-Excel,SPSS,Anlyse-it etc..
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