Discriminant analysis is one of the classical classification techniques used to discriminate a single categorical variable using multiple attributes. Discriminant analysis also assigns observations to one of the pre-defined groups based on the knowledge of the multi-attributes. When the distribution within each group is multivariate normal, a parametric method can be used to develop a discrimin...

While null space based linear discriminant analysis (NLDA) obtains a good discriminant performance, the ability easily suffers from an implicit assumption of Gaussian model with same covariance each class. Meanwhile, mixture model discriminant analysis, which is a good way for processing issues on multiple subclasses in each class, depends on human experience on the number of subclasses and has...

Data mining is a collection of analytical techniques to uncover new trends and patterns in massive databases. These data mining techniques stress visualization to thoroughly study the structure of data and to check the validity of the statistical model fit which leads to proactive decision making. Discriminant analysis is one of the data mining tools used to discriminate a single classification...

This paper presents a procedure for studying industrial performance and related issues such as changes in the wage structure. This procedure combines cluster analysis and discriminant analysis as a package, and applies this package to time series data. This enables us to organize industrial data into groups with similar wage or performance histories and then to extract summary time-series showi...

Measuring the effectiveness of corporate environmental reports, it being highly qualitative and less regulated, is often considered as a daunting task. The task becomes more complex if comparisons are to be performed. This study is undertaken to overcome the physical verification problems by implementing data mining technique. It further explores on the effectiveness by performing exploratory a...

Human diseases are abnormal medical conditions in which multiple biological components are complicatedly involved. Nevertheless, most contributions of research have been made with a single type of genetic data such as Single Nucleotide Polymorphism (SNP) or Copy Number Variation (CNV). Furthermore, epigenetic modifications and transcriptional regulations have to be considered to fully exploit t...

Lipid composition in cell membrane is closely associated with cell characteristics. Here, matrix-assisted laser desorption/ionization- Fourier transform ion cyclotron resonance mass spectrometry was employed to in situ determine membrane components of human mammary epithelial cells (MCF-10 A) and six different breast cancer cell lines (i.e., BT-20, MCF-7, SK-BR-3, MDA-MB-231, MDA-MB-157, and MD...

2 Classification of One-Dimensional Data 2 2.1 Linear Discriminant Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 2.1.1 Building the LDA Classifier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 2.1.2 Results of One-Dimensional LDA Classification . . . . . . . . . . . . . . . . . . . . . . 4 2.2 Quadratic Discriminant Analysis . . . . . ....