One Kind of Interval Support Vector Regression Algorithm and Its Application in Web Information Mining

Traditional support vector regression (SVR) algorithm can not handle training data which contain incomplete information. In order to overcome this shortcoming, this paper introduced the interval number to represent the incomplete information, and uses interval operation to replace the real operation, then an uncertainty support vector regression algorithm (USVR) was proposed, which can extend the SVR´s application area and improve its learning ability. We used the USVR algorithm to Web information mining experiment, and the results show that this algorithm is feasible and effective.