关键词: 极限学习机, 正则极限学习机, 期望风险, 结构风险, 经验风险

Abstract: Research on the model of extreme learning machine, a prediction model is proposed of extreme learning machine which is based on expected risk minimization. It’s basic idea is to consider both structure risk and expected risk at the same time, according to relationship between expected risk and empirical risk, converting expected risk into empirical risk, so that prediction model of extreme learning machine can be solve with minimizing expected risk. Using artificial data set and real data set of regression results, and compared with Extreme Learning Machine （ELM） and Regular Extreme Learning Machine （RELM） two kinds of algorithm performance. Experimental results show that the proposed method can effectively improve the generalization ability.

Key words: extreme learning machine, regularized extreme learning machine, expected risk, structure risk, empirical risk