Difficulty Assessment of Information System Migration Based on Gradient Boosting Tree Model
The paper proposes an approach for assessing the difficulty of information system migration in the context of information technology application innovation using a gradient boosting tree model.The method uses data from completed information system migration to train a model for assessing the difficulty of information system migration.Subsequently,data from the information system undergoing migration are input into the prediction model to achieve difficulty prediction.Experimental validation shows that the performance metrics of the information system migration difficulty assessment model,including AUC,precision,accuracy,recall,and F1 score,exhibit excellent overall performance.The micro-average and macro-average AUC values are 0.89 and 0.90,respectively.Therefore,this method holds significant practical value for the task of predicting the difficulty of information system migration in the context of information technology application innovation.It can assist decision-makers in formulating more accurate strategies for information system migration,thereby minimizing migration risks and saving migration costs.
gradient boosting treeinformation technology application innovationdifficulty assessment of information system migration
万方数据
维普
