Multi-Objective Genetic Algorithm for Multi-View Feature Selection

arXiv:2305.18352v2 Announce Type: replace-cross
Abstract: Multi-view datasets offer diverse forms of data that can enhance prediction models by providing complementary information. However, the use of multi-view data leads to an increase in high-dimensional data, which poses significant challenges for the prediction models that can lead to poor generalization. Therefore, relevant feature selection from multi-view datasets is important as it not only addresses the poor generalization but also enhances the interpretability of the models. Despite the success of traditional feature selection …

abstract algorithm arxiv challenges cs.ai cs.lg cs.ne data datasets diverse feature feature selection forms information leads multi-objective prediction prediction models type view