GSA‐Based Approach for Gene Selection from Microarray Gene Expression Data
Pintu Kumar Ram, Pratyay Kuila · 2021
Selection of gene is the most effective method that plays a vital role to detect the cancers. Due to non-redundant data set, it is very difficult to extract the optimal features or genes from microarray data. In this paper, we have proposed a new model to extract the best features subset with high accuracy based on Gravitational Search Algorithm (GSA) with machine learning classifiers. An extensive simulation is performed to evaluate the performance of the proposed algorithm. Simulation results are compared with the Particle Swarm Optimization Algorithm (PSO). The superiority of the proposed algorithm has been observed.