Research on performance prediction method based on decision level fusion
To solve the problems of low prediction accuracy and weak generalization ability of prediction model based on single method,a performance prediction method based on decision level fusion is proposed.Firstly,performance prediction models based on Gaussian process regression and partial least squares are constructed,respectively.Then,the weights of the two models are adjusted according to the prediction re-sults.Finally,the final prediction result is obtained by combining the decision weights of the two models.In order to verify the effectiveness and stability of the proposed method,a large number of random experi-ments are carried out on the real data of seven majors such as Chemistry and Chinese Language and Litera-ture in a university,the reaults which are compared with the mainstream prediction methods.The experi-ment results show that the proposed method has higher prediction performance and stability,and can pro-vide more credible decision support for teachers and students to improve teaching and learning methods.
education data miningfeature selectiondegree predictionpartial least squaregaussian process regression
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