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 ...

Linear dimensionality reduction techniques have been widely used in pattern recognition and computer vision, such as face recognition, image retrieval, etc. The typical methods include Principal Component Analysis (PCA) which is unsupervised and Linear Discriminant Analysis (LDA) which is supervised. Both of them consider an m1 × m2 image as a high dimensional vector in Rm1×m2 . Such a vector r...

The WeDiBaDis package provides a user friendly environment to perform discriminant analysis (supervised classification). WeDiBaDis is an easy to use package addressed to the biological and medical communities, and in general, to researchers interested in applied studies. It can be suitable when the user is interested in the problem of constructing a discriminant rule on the basis of distances b...

the conceptualization of resilience as a general or multidimensional construct and recognizing the inhibitors and facilitators of it are the main issues in the resilience literature. therefore, the present study investigated the discriminant variables of educational resilient and emotional resilient groups in person-focused approach, to examine the general or multidimensional construct of resil...

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...

This article utilizes data envelopment analysis (DEA) to estimate the productivity of the English and Welsh police forces and to determine whether there are categorical scale effects in policing using multiple discriminant analysis (MDA). The article demonstrates that by using DEA efficiency results it is possible to make inferences about the optimal size and structure of the English and Welsh ...

— The identi cation of epileptic seizures signi cantly relies on monitoring and visual analysis of large amounts of multichannel electroencephalographic (EEG) signals. With a goal of automating this time-consuming and subjective task, we develop a patient-speci c seizure recognition model for multi-channel scalp EEG signals. We differentiate between seizure and non-seizure periods by representi...

Many of the existing machine learning algorithms, both supervised and unsupervised, depend on the quality of the input characteristics to generate a good model. The amount of these variables is also important, since performance tends to decline as the input dimensionality increases, hence the interest in using feature fusion techniques, able to produce feature sets that are more compact and hig...

An even unimodular 72-dimensional lattice Γ having minimum 8 is constructed as a tensor product of the Barnes lattice and the Leech lattice over the ring of integers in the imaginary quadratic number field with discriminant −7. The automorphism group of Γ contains the absolutely irreducible rational matrix group (PSL2(7)× SL2(25)) : 2.