作者：Laber, Eric B.; Murphy, Susan A.
作者单位：University of Michigan System; University of Michigan
摘要：The estimated test error of a learned classifier is the most commonly reported measure of classifier performance. However, constructing a high-quality point estimator of the test error has proved to be very difficult. Furthermore, common interval estimators (e.g., confidence intervals) are based on the point estimator of the test error and thus inherit all the difficulties associated with the point estimation problem. As a result, these confidence intervals do not reliably deliver nominal cove...
作者：Crainiceanu, Ciprian M.; Caffo, Brian S.; Luo, Sheng; Zipunnikov, Vadim M.; Punjabi, Naresh M.
作者单位：Johns Hopkins University; University of Texas System; University of Texas Health Science Center Houston; University of Texas School Public Health; Johns Hopkins University
摘要：Images, often stored in multidimensional arrays, are fast becoming ubiquitous in medical and public health research. Analyzing populations of images is a statistical problem that raises a host of daunting challenges. The most significant challenge is the massive size of the datasets incorporating images recorded for hundreds or thousands of subjects at multiple visits. We introduce the population value decomposition (PVD), a general method for simultaneous dimensionality reduction of large pop...
