the main focus in this study is on data pre-processing, reduction in number of inputs or input space size reduction the purpose of which is the justified generalization of data set in smaller dimensions without losing the most significant data. in case the input space is large, the most important input variables can be identified from which insignificant variables are eliminated, or a variable ...

With the rapid development of nano-technology, a "colorimetric sensor array" (CSA) which is referred to as an optical electronic nose has been developed for the identification of toxicants. Unlike traditional sensors which rely on a single chemical interaction, CSA can measure multiple chemical interactions by using chemo-responsive dyes. The color changes of the chemo-responsive dyes are recor...

Linear Discriminant Analysis (LDA) and Multilinear Principal Component Analysis (MPCA) are leading subspace methods for achieving dimension reduction based on supervised learning. Both LDA and MPCA use class labels of data samples to calculate subspaces onto which these samples are projected. Furthermore, both methods have been successfully applied to face recognition. Although LDA and MPCA sha...

An electronic nose was used to distinguish between selected herb samples according to their family group species. This paper aims to evaluate the potential of using the electronic nose to characterize three groups of families of twelve herb species based on the discriminant analysis approach. The feature extraction involves the use of a signal processing technique that simplifies classification...

This paper analyses the bankruptcy prediction based on population of companies representative total business sector in Croatia. The representativity sample is achieved through propensity score matching full bankrupt and similar non-bankrupt companies. robust estimation carried out multiple discriminant analysis (MDA) logistic regression (logit). results indicate high classification accuracy bot...

Introduction. Iron deficiency anemia and thalassemia are the most common causes of microcytic anemia. Powerful statistical computer programming enables sensitive discriminant analyses to aid in the diagnosis. We aimed at investigating the performance of the multiple discriminant analysis (MDA) to the differential diagnosis of microcytic anemia. Methods. The training group was composed of 200 β ...

The proposed approach leads to analyzing the associations between a set of quantitative variables and several qualitative variables measured on a same set of individuals. In a decision-making context, the proposed method can be considered as a generalization of discriminant analysis to the multiple groups’ variables case. It’s described as a principal component analysis of the centres of gravit...

This study provides a financial analysis of those firms that during the recent period of economic recession and financial market turmoil beginning in December 2007 and continuing to June 2009 either maintained or increased the total compensation packages for their chief executive officers and other executives in their firms. Specifically, this analysis will test for significant differences in t...

Multiple-instance discriminant analysis (MIDA) is proposed to cope with the feature extraction problem in multiple-instance learning. Similar to MidLABS, MIDA is also derived from linear discriminant analysis (LDA), and both algorithms can be treated as multiple-instance extensions of LDA. Different from MidLABS which learns from the bag level, MIDA is designed from the instance level. MIDA con...