An Evolutionary Multiobjective Model and Instance Selection for Support Vector Machines With Pareto-Based Ensembles.

Support vector machines (SVMs) are among the most powerful learning algorithms for classification tasks. However, these algorithms require a high computational cost during the training phase, which can limit their application on large-scale datasets. Moreover, it is known that their effectiveness highly depends on the hyper-parameters used to train the model. With the intention of dealing with the...