Abstract
Due to the expansion of higher vocational college enrollment, the different quality of students and the high quality requirements of enterprise talents, this paper proposes an academic early warning system for higher vocational college students, which can be used for the early warning of students’ performance and improve the teaching quality. Firstly, the clustering algorithm is analyzed, and the parallel K-means algorithm is adopted in the general algorithm. During the startup and running of the program, the processing time of the algorithm is short and the total consumption of the system is small. Compared with the existing data mining technology, parallel K-means algorithm has good practicability and flexibility.
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