Support vector machines (SVMs), though accurate, are not preferred in applications requiring great classification speed, due to the number of support vectors being large. To overc...
S. Sathiya Keerthi, Olivier Chapelle, Dennis DeCos...
Abstract. The present study investigates a geometrical method for optimizing the kernel function of a support vector machine. The method is an improvement of the one proposed in [4...
The problem of extracting a minimal number of data points from a large dataset, in order to generate a support vector machine (SVM) classifier, is formulated as a concave minimiza...
The choice of the kernel function is crucial to most applications of support vector machines. In this paper, however, we show that in the case of text classification, term-frequenc...
A binary hierarchical classifier is proposed to solve the multi-class classification problem. We also require rejection of non-target inputs, which thus producing a very difficult...