Quantifying trends accurately despite classifier error and class imbalance

George Forman. Quantifying trends accurately despite classifier error and class imbalance. In Tina Eliassi-Rad, Lyle H. Ungar, Mark Craven, Dimitrios Gunopulos, editors, Proceedings of the Twelfth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Philadelphia, PA, USA, August 20-23, 2006. pages 157-166, ACM, 2006. [doi]

Abstract

Abstract is missing.