A Comprehensive Survey on Solving Clustering and Classification Problems Using Gravitational Search Algorithm

Gravitational search algorithm is a physics-based optimization algorithm inspired by Newton's law of gravitation and laws of motion. Both clustering and classification are two important steps in machine learning and getting expertise in them is the need of today's artificial intelligence era. Inventing new methods for mastering clustering and classification for reducing the complexity of the data is always welcome. This paper presents a review of applications of gravitational search algorithm and its variants for clustering and classification problems. In clustering, the GSA is used with various traditional clustering algorithms to find the interesting patterns in data and to divide the data set into different clusters. For solving classification problems, the GSA is hybridized with other swarm optimization algorithms to increase the classification accuracy and finding optimal classification rules.