Decision tree induction algorithms scale well to large datasets for their univariate and divide-and-conquer approach. However, they may fail in discovering effective knowledge when...
Giovanni Giuffrida, Wesley W. Chu, Dominique M. Ha...
Bayesian text classifiers face a common issue which is referred to as data sparsity problem, especially when the size of training data is very small. The frequently used Laplacian...
Software development techniques are continuously evolving with the goal of solving the main problems that still affect the building and maintenance of software systems: time, cost...
Consider the class of problems in which a target class is well-defined, and an outlier class is ill-defined. In these cases new outlier classes can appear, or the class-conditiona...
Thomas Landgrebe, David M. J. Tax, Pavel Pacl&iacu...
Hierarchical conditional random fields have been successfully applied to object segmentation. One reason is their ability to incorporate contextual information at different scales....
Xavier Boix, Josep M. Gonfaus, Joost van de Weijer...