Variable selection for cluster analysis is a difficult problem. The difficulty originates not only from the lack of class information but also the fact that high-dimensional data ...
Leonard K. M. Poon, Nevin Lianwen Zhang, Tao Chen,...
Abstract. This paper describes aspects of a training environment for crisis decision makers who, notoriously, operate in highly stressful and unpredictable situations. Training suc...
Gabriella Cortellessa, Rita D'Amico, Marco Pagani,...
—Adapting the hyperparameters of support vector machines (SVMs) is a challenging model selection problem, especially when flexible kernels are to be adapted and data are scarce....
For many supervised learning tasks it is very costly to produce training data with class labels. Active learning acquires data incrementally, at each stage using the model learned...
Model selection by the predictive least squares (PLS) principle has been thoroughly studied in the context of regression model selection and autoregressive (AR) model order estima...