New Media Interactive Design Visualization System Based on Artificial Intelligence Technology

Abstract

The experimental results show that the average cumulative contribution rate of this algorithm was 92.78%, while that of the traditional algorithm was 88.88%. In contrast, the average cumulative contribution rate of this algorithm was improved by 3.9%. In terms of classification accuracy, the average classification accuracy of this algorithm was 94.99%, while the traditional algorithm was 90.98%. In contrast, the average classification accuracy of this algorithm was improved by 4.01%. In terms of dimension reduction time, the average dimension reduction time of this algorithm was 3.46s, while that of the traditional algorithm was 6.43s. In contrast, the average dimension reduction time of this algorithm was shortened by 2.97s. It can be seen from the data that the improved PCA algorithm can effectively improve the classification accuracy and cumulative contribution rate of the visualization system, shorten the dimension reduction time, and improve the system's ability to process data.