Home > Publications . Search All . Browse All . Country . Browse PSC Pubs . PSC Report Series

PSC In The News

RSS Feed icon

Former trainee Herbert says residential squatters may be a good thing

Work by Couper, Farley et al. shows impact of racial composition on neighborhood choice

Thompson details killings and shaping of official narrative in 1971 Attica prison uprising

More News

Highlights

Michigan ranked #12 on Business Insider's list of 50 best American colleges

Frey's new report explores how the changing US electorate could shape the next 5 presidential elections, 2016 to 2032

U-M's Data Science Initiative offers expanded consulting services via CSCAR

Elizabeth Bruch promoted to Associate Professor

Next Brown Bag

PSC Brown Bags
will resume fall 2016

Adaptive Confidence Intervals for the Test Error in Classification

Publication Abstract

Laber, Eric B., and Susan A. Murphy. 2011. "Adaptive Confidence Intervals for the Test Error in Classification." Journal of the American Statistical Association, 106(495): 904-913.

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 coverage. In contrast, we directly construct the confidence interval by using smooth data-dependent upper and lower bounds on the test error. We prove that, for linear classifiers, the proposed confidence interval automatically adapts to the nonsmoothness of the test error, is consistent under fixed and local alternatives, and does not require that the Bayes classifier be linear. Moreover, the method provides nominal coverage on a suite of test problems using a range of classification algorithms and sample sizes. This article has supplementary material online.

DOI:10.1198/jasa.2010.tm10053 (Full Text)

PMCID: PMC3285493. (Pub Med Central)

Browse | Search : All Pubs | Next