DISCRIMINANT FUNCTIONS AND THEIR MISCLASSIFICATION ERRORS

Asymptotic Evaluation of the Probabilities of Misclassification by Linear Discriminant Functions By

Voronoi networks and their probability of misclassification

Nearest neighbor classifiers that use all the training samples for classification require large memory and demand large online testing computation. To reduce the memory requirements and the computation cost, many algorithms have been developed that perform nearest neighbor classification using only a small number of representative samples obtained from the training set. We call the classificati...

Differential misclassification arising from nondifferential errors in exposure measurement.

Misclassification into exposure categories formed from a continuous variable arises from measurement error in the continuous variable. Examples and mathematical results are presented to show that if the measurement error is nondifferential (independent of disease status), the resulting misclassification will often be differential, even in cohort studies. The degree and direction of differential...

Bayesian Inference for Categorical Data with Misclassification Errors

In epidemiological studies, observed data are often collected subject to misclassification errors. In this paper, we discuss the Bayesian estimation for contingency table with misclassification errors. Employing the exact Bayesian computations to obtain posterior means as estimates, we are faced with computational difficulties. In order to find the posterior distribution, we apply the data augm...

ANALYSIS OF CATEGORICAL DATA WITH MISCLASSIFICATION ERRORS by CHUN-

Errors in the collection of data are obstacles to analysis because the underlying misclassification mechanism is usually unknown. Many authors have investigated this problem. In this paper, we shall concentrate on the analysis of contingency tables which are subject to misclassification errors. A general misclassification framework for multi-dimensional contingency tables is proposed. Base on t...