Comment on "Adaptive Confidence Intervals for the Test Error in Classification"

TitleComment on "Adaptive Confidence Intervals for the Test Error in Classification"
Publication TypeJournal Article
Year of Publication2011
AuthorsGoldberg, Yair, and Michael R. Kosorok
JournalJ Am Stat Assoc
Volume106
Issue495
Pagination920-924
Date Published2011 Jul 01
ISSN0162-1459
Abstract

Inspired by the non-regular framework studied in Laber and Murphy (2011), we propose a family of adaptive classifiers. We discuss briefly their asymptotic properties and show that under the non-regular framework these classifiers have an "oracle property," and consequently have smaller asymptotic variance and smaller asymptotic test error variance than those of the original classifier. We also show that confidence intervals for the test error of the adaptive classifiers, based on either normal approximation or centered percentile bootstrap, are consistent.

DOI10.1198/jasa.2011.tm11320
Alternate JournalJ Am Stat Assoc
Original PublicationComment on "Adaptive confidence intervals for the test error in classification"
PubMed ID23741079
PubMed Central IDPMC3670236
Grant ListP01 CA142538 / CA / NCI NIH HHS / United States
P01 CA142538-02 / CA / NCI NIH HHS / United States
Project: