The selection of relevant variables in the model is one of the important problems in regression analysis. Recently, a few methods were developed based on a model free approach. A multilayer feedforward neural network model was proposed for developing variable selection in regression. A simulation study and real data were used for evaluating the performance of proposed method in the presence of outliers, and multicollinearity.
Kamble, Tejaswi S. and Kashid, Dattatraya N.
"Variable Selection in Regression using Multilayer Feedforward Network,"
Journal of Modern Applied Statistical Methods:
1, Article 33.
Available at: http://digitalcommons.wayne.edu/jmasm/vol15/iss1/33