Multi-Objective Semi-Supervised Feature Selection and Model Selection Based on Pearson's Correlation Coefficient [chapter]

Frederico Coelho, Antonio Padua Braga, Michel Verleysen
2010 Lecture Notes in Computer Science  
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.
doi:10.1007/978-3-642-16687-7_67 fatcat:izay33hhazc3rjpfwxx6iuqq24