Abstract
In this study, the scientific creativity of engineering students was measured. The quality of data was analyzed with Generalizability Theory. The modeling was conducted with BP_Adaboost RT, and compared with the model of multiple linear regression and single BP network. The results showed that Generalizability Theory could be applied to analyze the scientific creativity data. The quality of data would affect the predictive accuracy of the model. BP_Adaboost RT model was better than other two models.
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