The Algorithm of Student Grade Evaluation Based on Clustering

Aiming at the current assessment methods of college courses, an algorithm of student grade evaluation based on clustering is proposed. Using course performance data from multiple platforms, after preprocessing and integration, K-means algorithm is used to classify the results, and then Mahalanobis distance is used to achieve the grade evaluation of the results. The experimental results show that the proposed algorithm has a good effect, the algorithm has a guiding significance for the students in the edge of classification, and has a good application value.