Research on Bagging regression algorithm based on attribute weight
An attribute weight based new regression algorithm called Bagging regression algorithm is proposed. The support vector regression or principal component analysis is used to value a certain weight for the sample data to show the attribute con?tribution in the regression process. And then the multiple attribute subsets for training were constructed according to the weights of different attributes. The constructing process of the attribute subsets is conducted in accordance with the weights of different attributes as a percentage of the total weight to determine the probability,which makes the attribute with great regression contri?bution possibly be selected in the attribute subsets for training. The attribute subsets are trained to generate the corresponding multiple regression sub?models. The assembly of these sub?models is the final model trained by the Bagging regression algorithm based on attribute weight.
support vector machineattribute weightensemble learningprincipal component analysisregression algorithm
国家科技期刊平台
NSTL
万方数据
维普
