Abstract: Extreme learning machine ridge regression(ELMRR) learning algorithm of ridge parameter optimization is proposed to solve the problem that oddity solution possibly exists in ELM learning algorithm.The algorithm makes use of ridge regression instead of the previous linear regression,and uses particle swarm optimization algorithm to optimize ridge parameter according to root mean square error(RMSE).Simulation experiment is performed for analyzing function regression and classification,and the effectiveness of this method is validated.The experimental results show that the algorithm improves predictive performance of ELM and overcomes the main flaw that it is difficult to obtain the ridge parameter in traditional ridge regression.