Using Support Vector Machines for MiRNA Identification

In binary classification problems, two classes of data seem to be different from each other. It is expected more complicated due the clusters in class also tend different. Traditional algorithms as Support Vector Machine (SVM) or Twin (TWSVM) cannot sufficiently exploit structural information with cluster granularity data, cause limitation on capability simulation trends. Structural (S-TWSVM) e...

In this chapter, we discuss two possible ways of improving the performance of the SVM, using geometric methods. The first adapts the kernel by magnifying the Riemannian metric in the neighborhood of the boundary, thereby increasing separation between the classes. The second method is concerned with optimal location of the separating boundary, given that the distributions of data on either side ...

X. CAO{{, J. CHEN*{, B. MATSUSHITA§, H. IMURA" and L. WANG{{ {Key Laboratory of Environment Change and Natural Disaster, Ministry of Education of China, College of Resource Science and Technology, Beijing Normal University, Beijing, 100875, China {Graduate School of Engineering, Nagoya University, Nagoya 464-8603, Japan §Graduate School of Life and Environmental Sciences, University of Tsukuba,...

EYE DETECTION USING DISCRIMINATORY FEATURES AND AN EFFICIENT SUPPORT VECTOR MACHINE

The purpose of the evaluation is to reflect on whether education provides a good environment and conditions for development students effect teaching practicability talents cultivated by society. When art evaluated, number positive outcomes have been achieved in terms education, including improvement as whole, talent, stronger role educational social communities concerned about quality education...