We present a new method that we call generalized discriminant analysis (GDA) to deal with nonlinear discriminant analysis using kernel function operator. The underlying theory is close to the support vector machines (SVM) insofar as the GDA method provides a mapping of the input vectors into high-dimensional feature space. In the transformed space, linear properties make it easy to extend and g...

classical lbp such as complexity and high dimensions of feature vectors that make it necessary to apply dimension reduction processes. in this paper, we introduce an improved lbp algorithm to solve these problems that utilizes fast pca algorithm for reduction of vector dimensions of extracted features. in other words, proffer method (fast pca+lbp) is an improved lbp algorithm that is extracted ...

This paper proposes a method for performing fuzzy multiple discriminant analysis on groups of crisp data and determining the membership function of each group by minimizing the classi.cation error using a genetic algorithm. Euclidean distance is used to measure the similarity between data points and de.ning membership functions. A numerical example is provided for illustration. The numerical ex...

rapid exploratory field survey, to identify indigenous chicken ecotypes was conducted in north gondar zone of ethiopia. chicken ecotypes including necked neck, gasgie and gugut from quara, alefa and tache armacheho districts were identified, respectively. morphological variations among the three study populations and nine measurable traits were evaluated. general linear model, canonical discrim...