This work proposes the use of maximal variation analysis for feature selection within least squares support vector machines for survival analysis. Instead of selecting a subset of ...
Vanya Van Belle, Kristiaan Pelckmans, Johan A. K. ...
Frequently, the number of input variables (features) involved in a problem becomes too large to be easily handled by conventional machine-learning models. This paper introduces a c...
Fernando Mateo, Dusan Sovilj, Rafael Gadea Giron&e...
In this paper, we present a proposal for Patients’ Mobile Monitoring. This framework enables the definition and generation of profiles, modules and communication structures betwe...
Vladimir Villarreal, Javier Laguna, Silvia L&oacut...
Abstract— Meta-Learning has been used to predict the performance of learning algorithms based on descriptive features of the learning problems. Each training example in this cont...
— Gene expression based cancer classification using classifier ensembles is the main focus of this work. A new ensemble method is proposed that combines predictions of a small ...