Ncibi, KaisDjenina, AmorSadraoui, TarekMILI, Faycel2023-10-022023-10-0220172602-5655http://hdl.handle.net/123456789/16828Function expansion was used to expand initial features based on a non linear transformation. Many known expansion functions are found such the trigonometric, the polynomial, the Legendre polynomial, the power series, the exponential and the logarithmic transformation. This paper present a comparison between different expansion functions based on mutual information and different performance functions. We propose a new expansion process able to improve the correspondent mutual information and the final performance. The process was tested; using different benchmark databases, and shows his ability to improve results of classification problemsenFunction expansionMultilayer perceptronClassificationMutual informationFeatures selectionA NEW HYBRID EXPANSION FUNCTION BASED MUTUAL INFORMATION FOR A MULTILAYER NEURAL NETWORKS OPTIMIZATIONArticle