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Samples in periodicals archive:
The foundations of Support Vector Machines (SVM) have been developed by Vapnik (1995) and are gaining popularity due to many attractive features, and promising empirical performance.
Support Vector Machine (SVM) is one of the new methods using in data mining.
A gentle introduction to support vector machines in biomedicine; v.
The Chinese researchers propose a fast quasi-dense matching algorithm, a support vector machine method for image denoising, a distributed space-time coding scheme for wireless relay networks, and earthquake aftershock prediction with K nearest neighbor.
The recent results in pattern recognition have shown that support vector machine (SVM) classifiers often have superior recognition rates in comparison to other classification methods.
The support vector machines SVM were proposed originally in the context of machine learning, for classification problems on typically large sets of data which have an unknown dependency on possibly many variables.
A new Neural Network learning technique that utilizes the SRM principle is so called Support Vector Learning.
Furthermore, the p -class subproblemss are solved by support vector ordinal regression machine (SVORM).