  Regression analysis is an important machine learning task used for predictive
analytic in business, sports analysis, etc. In regression analysis,
optimization algorithms play a significant role in search the coefficients in
the regression model. In this paper, nonlinear regression analysis using a
recently developed meta-heuristic Multi-Verse Optimizer (MVO) is proposed. The
proposed method is applied to 10 well-known benchmark nonlinear regression
problems. A comparative study has been conducted with Particle Swarm Optimizer
(PSO). The experimental results demonstrate that the proposed method
statistically outperforms PSO algorithm.
