关键词: 支持向量机, 规则提取, 回归树

Abstract: The kernel function of Support Vector Machine（SVM） used of inner product causes “black box” problem. Currently, the research of “black box” mainly adopts the rule extraction method to solve classification problems, but the problem of the regression is rarely mentioned. This paper tries to propose an SVM regression rule extraction method based on the regression tree algorithm. The algorithm takes full advantage of the special properties of support vectors and the advantage of the regression tree, establishes tree model based on support vectors. It successfully extracts high decision-making capacity, including less variables, a small amount of calculation and easy to read rules. Through training and testing the standard data set “Auto MPG” and the actual production data of coal to methanol, comparison of results with other algorithms shows that, the extracted regression rules in the training accuracy and prediction accuracy have a certain degree of improvement.

Key words: support vector machine, rules extraction, regression tree