University Financial Management and Decision Analysis based on Decision Tree Algorithm

With the expansion of the enrollment scale of colleges and universities year by year, the volume of financial data of colleges and universities is also growing. In order to make the financial management of colleges and universities more scientific and reasonable, we can consider applying business intelligence, data warehouse, data mining technology, decision support system and other technologies to the financial decision-making process of colleges and universities. This paper aims at the large amount of financial data generated by the university financial management system, based on the decision tree algorithm, combined with data mining and analysis technology, to realize the university financial management and decision-making, and provide effective support for the university management operation. Decision analysis is the process of analyzing decisions and their consequences to determine whether they are the best course of action. Decision analysis has been studied for many years, but the research on this topic has increased recently. In recent years, there has been a lot of research in the field of university financial management and decision analysis. This paper will discuss how these two fields combine to create a new field, namely University Financial Management and Decision Analysis (UFMDA). At first, the paper summarizes the current situation and existing problems of university financial management and decision-making methods. According to the characteristics and decision-making process of university financial data, the paper studies and analyzes the advantages and disadvantages of clustering algorithm and classification algorithm, and proposes a metric-based C4 5 Improved decision tree algorithm.