Multi-Objective Semi-supervised Feature Selection and Model Selection based on Pearson's Correlation Coefficient
Frederico Gualberto Ferreira Coelho, Antônio P. Braga, Michel Verleysen · 2010
www.uclouvain.be Abstract. This paper presents a Semi-Supervised Feature Selection Method based on a univariate relevance measure applied to a multiobjective approach of the problem. Along the process of decision of the optimal solution within Pareto-optimal set, atempting to maximize the relevance indexes of each feature, it is possible to determine a minimum set of relevant features and, at the same time, to determine the optimal model of the neural network. Keywords: Semi-supervised, feature selection, Pearson, Relief. 1