Takuma Udagawa, Aashka Trivedi, et al.
EMNLP 2023
This report investigates the behavior of the a posteriori probabilities for classification problems in which the observations are not identically distributed. Some basic properties of the a posteriori probabilities are presented; then, it is shown that for each class the a posteriori probability converges a.s. to a random variable. Conditions are given for a.s. convergence of the a posteriori probability to 1 for the true class (and to 0 for all other classes). The results are illustrated for the case of two classes and binary observations, and finally a numerical example is presented. © 1977.
Takuma Udagawa, Aashka Trivedi, et al.
EMNLP 2023
Arnon Amir, Michael Lindenbaum
IEEE Transactions on Pattern Analysis and Machine Intelligence
Joseph Y. Halpern
aaai 1996
Rie Kubota Ando
CoNLL 2006