Design and Implementation of Online Credit Evaluation System Based on Transfer Learning

This paper mainly studies the design and implementation of the online credit evaluation system based on transfer learning, and makes improvements in view of the slow speed and simple results of the original evaluation system, which cannot accurately evaluate. In this paper, the basic algorithm of transfer learning is studied in depth, from the algorithm principle, cognitive analysis, algorithm model and so on. The basic algorithm of meta learning is introduced. The parameters of twin network tracking algorithm are studied to understand the application significance and function of different parameters in the algorithm. The performance of the new credit evaluation system is tested by combining the meta-learning and twin network tracking, and the test results are compared with those of the original evaluation system, which proves that the new credit evaluation system has better performance in terms of capability and accuracy. Therefore, this paper establishes an online credit evaluation system with transfer learning ability. The final result shows that the new online credit evaluation system is more intelligent and has a unique and perfect evaluation method.