Optimization of business management model based on decision tree model

Abstract

For data mining technology systems, decision tree algorithms are applied more frequently and belong to the category of classification algorithm management itself, which in most cases presents the results by means of if-then rules. As a type of decision tree algorithm, the C4.5 algorithm is not only highly accurate but also very easy to understand, comparing with the ID3 algorithm, which introduces the concept of information gain rate into it. In this paper, by conducting theoretical research activities, we finally chose to use C4.5 algorithm for performance appraisal result evaluation, data pre-processing and sub-attribute confirmation. The system is developed using B/S architecture, relying on visualization tools, dynamic web pages and other technical means to create a project management system and platform, which can meet the requirements of enterprise managers for employee performance appraisal results analysis. The system involves many modules, such as information storage, task management, report generation, and information visualization. Under the condition that several modules work together, it can basically achieve the functional goals of project management, employee information filling, performance appraisal mechanism construction, report generation, etc. With the decision tree algorithm as the core technology, the accuracy of project management information is comprehensively improved to meet the requirements of scientificity and validity, and after achieving the goal of data visualization, the enterprise can gradually realize the goal of management mechanism construction by relying on big data technology.