In classification problems, Support Vector Machines maximize the margin of separation between two classes. While the paradigm has been successful, the solution obtained by SVMs is...
Many data mining applications can benefit from adapting existing classifiers to new data with shifted distributions. In this paper, we present Adaptive Support Vector Machine (Ada...
In this paper we describe a new method to reduce the complexity of support vector machines by reducing the number of necessary support vectors included in their solutions. The red...
In this paper, we utilize a simple support vector machine to identify commercial electronic mail. The use of a personalized dictionary for model training provided a classification...
Matthew Woitaszek, Muhammad Shaaban, Roy Czernikow...
In this paper, a method to generalize previously proposed Chebyshev Kernel function is presented for Support Vector Classification in order to obtain more robust and higher classi...