Mohamed Abdel-Basset1, Reda Mohamed1, Ripon K. Chakrabortty2, Michael J. Ryan2, Yunyoung Nam3,*, Mohamed Abouhawwash4,5
CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 2883-2901, 2021, DOI:10.32604/cmc.2021.017854
Abstract This paper proposes a new pre-processing technique to separate the most effective features from those that might deteriorate the performance of the machine learning classifiers in terms of computational costs and classification accuracy because of their irrelevance, redundancy, or less information; this pre-processing process is often known as feature selection. This technique is based on adopting a new optimization algorithm known as generalized normal distribution optimization (GNDO) supported by the conversion of the normal distribution to a binary one using the arctangent transfer function to convert the continuous values into binary values. Further, a novel restarting strategy (RS) is proposed… More >
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