In supervised learning, we commonly assume that training and test data are sampled from the same distribution. However, this assumption can be violated in practice and then standa...
Background: Cross-validation (CV) is an effective method for estimating the prediction error of a classifier. Some recent articles have proposed methods for optimizing classifiers...
Abstract. Some issues about the generalization of ANN training are investigated through experiments with several synthetic time series and real world time series. One commonly acce...
Wen Wang, Pieter H. A. J. M. van Gelder, J. K. Vri...
Abstract--We consider the adaptive detection of a signal of interest embedded in colored noise, when the environment is nonhomogeneous, i.e., when the training samples used for ada...
This paper proposes a novel approach to the problem of training classifiers to detect and correct grammar and usage errors in text by selectively introducing mistakes into the tra...