Cluster Evaluation of Accounting COMET Professional Ability Training Based on Apriori Algorithm

Purpose: In today's world, economic globalization and the new technological revolution have posed serious challenges to the vocational education system. Countries around the world have reformed the content of vocational education, from the original simple job skills training to comprehensive vocational ability training. Method: This article used the Apriori algorithm to conduct cluster analysis on the training of accounting COMET professional abilities, and a total of 5 sets of experiments were conducted. Result: The experimental results showed that the Apriori algorithm-based vocational ability training improved clustering accuracy and compatibility to 88.8% and 85%, respectively, while also reducing sensitivity. Conclusion: From this, it can be seen that using the Apriori algorithm for data mining can mine different types of association rules at different levels, which is beneficial for improving the effectiveness of accounting COMET vocational training.