An improved fast classification algorithm based on Brain Emotional Learning (BEL) and Genetic Algorithm (GA) is proposed to enhance the accuracy and efficiency.Inspired by the neurobiology research of emotional learning mechanism in amygdala and orbitofrontal cortex

the BEL model is constructed to mimic the mechanism of emotional stimulus processing in human brain.For the short path in the emotional brain

BEL can speed up the learning process.Furthermore

the learning weights in BEL are optimized by GA in order to improve the accuracy.Experiments using UCI datasets are performed

by which the results show that GA-BEL classification obtains higher accuracy and less computing time compared to other classifiers

in both small and large sample datasets.