Cart (Loading....) | Create Account
Close category search window
 

On Strong Consistency of Model Selection in Classification

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Suzuki, J. ; Dept. of Math., Osaka Univ.

This paper considers model selection in classification. In many applications such as pattern recognition, probabilistic inference using a Bayesian network, prediction of the next in a sequence based on a Markov chain, the conditional probability P(Y=y|X=x) of class yisinY given attribute value xisinX is utilized. By model we mean the equivalence relation in X: for x,x'isinXx~x'hArrP(Y=y|X=x)=P(Y=y|X=x'), forall yisinY. By classification we mean the number of such equivalence classes is finite. We estimate the model from n samples zn=(xi,yi)i=1 n isin(XtimesY)n, using information criteria in the form empirical entropy H plus penalty term (k/2)dn (the model such that H+(k/2)dn is minimized is the estimated model), where k is the number of independent parameters in the model, and {dn}n=1 infin is a real nonnegative sequence such that lim supndn/n=0. For autoregressive processes, although the definitions of H and k are different, it is known that the estimated model almost surely coincides with the true model as nrarrinfin if {dn}n=1 infin>{2loglogn}n=1 infin, and that it does not if {dn}n=1 infin<{2loglogn}n=1 infin (Hannan and Quinn). The problem whether the same property is true for classification was open. This paper solves the problem in the affirmative

Published in:

Information Theory, IEEE Transactions on  (Volume:52 ,  Issue: 11 )

Date of Publication:

Nov. 2006

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.