Ensemble methods like bagging and boosting that combine the decisions of multiple hypotheses are some of the strongest existing machine learning methods. The diversity of the memb...
Properties of ensemble classification can be studied using the framework of Monte Carlo stochastic algorithms. Within this framework it is also possible to define a new ensemble c...
Various methods for ensemble selection and classifier combination have been designed to optimize the results of ensembles of classifiers. Genetic algorithm (GA) which uses the div...
Albert Hung-Ren Ko, Robert Sabourin, Alceu de Souz...
This paper presents a new method for constructing ensembles of classifiers based on immune network theory, one of the most interesting paradigms within the field of artificial imm...
By far, the support vector machines (SVM) achieve the state-of-theart performance for the text classification (TC) tasks. Due to the complexity of the TC problems, it becomes a ch...