It is difficult to adapt discriminative classifiers, particularly kernel based ones such as support vector machines (SVMs), to handle mismatches between the training and test da...
Support vector machines (SVMs) are regularly used for classification of unbalanced data by weighting more heavily the error contribution from the rare class. This heuristic techn...
We propose to solve a text categorization task using a new metric between documents, based on a priori semantic knowledge about words. This metric can be incorporated into the def...
— Effective use of support vector machines (SVMs) in classification necessitates the appropriate choice of a kernel. Designing problem specific kernels involves the definition...
Steinn Gudmundsson, Thomas Philip Runarsson, Sven ...
In dealing with large datasets the reduced support vector machine (RSVM) was proposed for the practical objective to overcome the computational difficulties as well as to reduce t...