Design of Financial Data Feature Forecast System Based on Clustering Algorithm

Abstract

The great success of computer technology in various fields has led to the great development of relational database systems. In the face of exponential growth in data, data processing and analysis are particularly important. How to extract useful business information from massive financial data is also a topic. This paper studies the financial data feature prediction of the clustering algorithm, understands the relevant theories of the financial data feature prediction system based on the literature, and then designs the financial data feature prediction system based on the clustering algorithm, and then designs the design of the financial data feature prediction system. The system is tested, and the test results show that the standard deviation of the overall false alarm rate of the system in this paper is 1.76%; the standard deviation of the overall false alarm rate of the system is 1.53%.