Abstract. Trained support vector machines (SVMs) have a slow runtime classification speed if the classification problem is noisy and the sample data set is large. Approximating the...
Abstract. In our previous work we have shown that Mahalanobis kernels are useful for support vector classifiers both from generalization ability and model selection speed. In this ...
Recursive Feature Elimination RFE combined with feature-ranking is an effective technique for eliminating irrelevant features. In this paper, an ensemble of MLP base classifiers wi...
This paper introduces a generic theoretical framework for predictive learning, and relates it to data-driven and learning applications in earth and environmental sciences. The iss...
Vladimir Cherkassky, Vladimir M. Krasnopolsky, Dim...
We propose a novel similarity measure, called the correntropy coefficient, sensitive to higher order moments of the signal statistics based on a similarity function called the cro...
Jian-Wu Xu, Hovagim Bakardjian, Andrzej Cichocki, ...