Research on Multidimensional Data Calculation Analysis and Optimization Path of Teachers’ Practical Teaching Cultivation Innovation Mechanisms under Digital Empowerment of Education

With the development of big data and education informatization, education reform and talent cultivation mode are facing digital reform.In this paper, the important feature selection algorithm based on random forest is used to select the relevant features that affect the application effect of teachers' practice teaching cultivation and innovation mechanism, which lays the foundation for constructing the practice teaching data mining model based on LightGBM.Then the data processed by feature selection is preprocessed and standardized, and then the processed data is partitioned and the model is trained in turn to get the prediction results.The LightGBM-based practical teaching data mining model was compared with other classification models in different datasets, and the experimental results showed that the model in this paper has an advantage over other classification models in a number of evaluation indexes, with the highest accuracy rate of 13.07%, and the model data mining results accurately locate the open innovation experimental indexes that have a lower score of importance to students' development, and provide a good basis for the optimization of teaching paths and students' development., which provides ideas for the optimization of teaching paths and the improvement of the impact of students' future development.