ROC curve estimation and hypothesis testing: applications to breast cancer detection

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The receiver operating characteristic (ROC) formulation of the two class signal detection problem is well known with its present theory being based on decision theory and psychophysics. Statistical procedures developed for analyzing these human observer detection experiments can be extended to analyzing pattern recognition experiments with computer based classification schemes. This article presents an introduction to statistical estimation and hypothesis testing methodology, which can be employed in analyzing the performance of various classifiers. The methodology will be illustrated by analyzing the performance of two classifiers in a breast cancer detection task.

论文关键词:ROC analysis,ROC curve estimation,Error estimation,Logistic function detection,Linear discriminant function,K-nearest neighbor

论文评审过程:Received 1 June 1981, Available online 19 May 2003.

论文官网地址:https://doi.org/10.1016/0031-3203(82)90077-2