Dimensionality Reduction and Visualization in Public Management Research from the Perspective of Algorithm Recommendation

Abstract

With the development of computer technology, algorithm recommendation systems have been widely used in intelligent transportation, urban planning, and other fields. Aiming at the current problems in public management in China, this paper proposes a dimensionality reduction calculation method, and uses the improved particle swarm optimization algorithm to analyze and evaluate the dimensionality reduction process. With the expectation of providing some reference value and ideas for solving practical application problems, a corresponding relationship equation is established with the minimum expected value as the objective function to solve the corresponding optimal solution, the evaluation results of system performance indicators and comprehensive scoring criteria under relevant parameters and constraints are given. The test results show that the visualization effect of the dimensionality reduction visualization model for public management research based on the algorithm recommendation perspective is over 90%.