This study found that machine learning algorithms can optimize the efficiency of data structure analysis systems, thus completing the design and construction of a mature data structure analysis system.
In current computer science, data structure analysis is undoubtedly one of the most important tasks. With the development of the times and technology, data structure analysis is facing many challenges. The main issue in this process is feature selection. Therefore, this article chose machine learning algorithms to optimize it. In the end, this article also verified the feasibility of the method of this paper through a comparative experiment between an intelligent data structure analysis system based on machine learning algorithms and a conventional system. The final result was that the average resource utilization rate of the intelligent system was 93.13%, while the average resource utilization rate of the conventional system was 86.45%, with a significant difference. Moreover, the resource utilization rate of the conventional system continued to decline over time, leading to lower work efficiency. Therefore, this study found that machine learning algorithms can optimize the efficiency of data structure analysis systems, thus completing the design and construction of a mature data structure analysis system.