In model selection procedures in supervised learning, a model is usually chosen so that the expected test error over all possible test input points is minimized. On the other hand...
This paper describes the development of a predictive model for corporate insolvency risk in Australia. The model building methodology is empirical with out-ofsample future year te...
Abstract— A novel nonparametric paradigm to model identification has been recently proposed where, in place of postulating finite-dimensional models of the system transfer func...
Gianluigi Pillonetto, Alessandro Chiuso, Giuseppe ...
In order to build predictors of the maintainability of evolving software, we first need a means for measuring maintainability as well as a training set of software modules for whi...
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 ...