A competitive Neyman-Pearson approach to universal hypothesis testing with applications.

Evgeny Levitan Neri Merhav

Published in: IEEE Trans. Inf. Theory (2002)

Keyphrases

hypothesis testing
neyman pearson
likelihood ratio
neural network
type ii
hypothesis test
support vector machine
statistical tests
likelihood ratio test
robust statistical
binary classification
null hypothesis
training data
feature space
error rate
image segmentation
hypothesis tests