By Topic

Almost everywhere convergence of a recursive regression function estimate and classification (Corresp.)

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

2 Author(s)

It is shown that the recursive kernel estimate of the regression function E(Y|X = x) is consistent at almost every x(\mu) regardless of the distribution \mu of X . Thus the result is distribution-free. From this we show that the risk for a suitable classification rule derived from the estimate converges to Bayes' risk, no matter what the class distributions are.

Published in:

Information Theory, IEEE Transactions on  (Volume:30 ,  Issue: 1 )