There are well-established methods for reducing the number of support vectors in a trained binary support vector machine, often with minimal impact on accuracy. We show how reduce...
In this work, we present a new model for a Recurrent Support Vector Machine. We call it intrinsic because the complete recurrence is directly incorporated within the considered opt...
Background: Protein subcellular localization is an important determinant of protein function and hence, reliable methods for prediction of localization are needed. A number of pre...
The large number of genes and the relatively small number of samples are typical characteristics for microarray data. These characteristics pose challenges for both sample classif...
In recent years, research and development in the field of machine learning and classification techniques have gained paramount importance. The future generation of intelligent e...