Among the various discriminant analysis (DA) methods, researchers have investigated several directions in this area: statistics, econometrics, computer data mining technologies and mathematical programming. Recently, as a nonparametric mathematical programming approach, Data envelopment analysis has been applied in DA area and received great attention. In this paper, we propose a new discrimina...

ABC analysis is a popular and effective method used to classify inventory items into specific categories that can be managed and controlled separately. In traditional ABC analysis the inventory items are categorized in to A ,B and C classes based on the annual dollar usage. The annual dollar usage is determined as the product of unit cost of each item and its annual demand. The items are arrang...

Business failures can cause financial damages to investors, creditors, or even society. For this reason bankruptcy prediction is one of the most challenging tasks in the field of financial decisionmaking. Business failure prediction has been an active research area since the 60s. The work of Beaver (1966) who performed univariate analysis of financial ratios and the work of Altman (1968) who em...

A method for fully automating the measurement of various neurological structures in MRI is presented. This technique uses an atlas-based trained maximum likelihood classifier. The classifier requires a map of prior probabilities, which is obtained by registering a large number of previously classified data sets to the atlas and calculating the resulting probability that each represented tissue ...

Discriminant analysis for two data sets in IR d with probability densities f and g can be based on the estimation of the set G = fx : f(x) g(x)g. We consider applications where it is appropriate to assume that the region G has a smooth boundary. In particular, this assumption makes sense if discriminant analysis is used as a data analytic tool. We discuss optimal rates for estimation of G.