A benchmark study regarding Extreme Learning Machine, modified versions of Naïve Bayes Classifier and Fast Support Vector Classifier

This paper aims to highlight the performances and advantages of three improved and fast AI algorithms that are mainly used in classification problems suitable for various fields. The discussions regarding the benchmark results appeal to the Modified version of Radial Basis Function (RBF-M) mentioned in the paper as Fast Support Vector Classifier (FSVC) or Fast Support Vector Machine, Extreme Learning Machine (ELM) with its randomness model and a reduced complexity version for Naïve Bayes (NB) algorithm. The performance studies conducted shows a good capacity of these networks to be used in medical embedded systems.