Abstract: This paper proposed a fast support vector regression algorithm. This algorithm converts the ctuadratic programming problems(Qpps) with pair groups of linear inequality constraints to two small size Qpps with only one group of linear inequality constraints. Each of the small size Qpps is solved by an iterative algorithm. The iterative algorithm converges from any starting point and does not need any quadratic optimization packages. Thus this algorithm is fast.The experimental results on several benchmark datasets demonstrate the effectiveness of the proposed algorithm.

Key words: Support vector regression, Lagrange support vector machine, Twin support vector regression, Iterative algorithm