Application and Functional simulation of data mining technology in Hadoop cloud platform based on improved algorithm

Abstract

Data mining algorithms can process target data and extract useful hidden information, which is helpful for decision making. However, current mining algorithms have some shortcomings such as time-consuming processing of big data or inability to process massive data. Since data mining technology cannot be used in the traditional cloud platform environment, it is necessary to improve the algorithm to make it more adaptable to the cloud platform environment. By analyzing the actual application process of BP classification algorithm, this paper describes the practicability of BP classification algorithm, analyzes the process of data mining based on Hadoop cloud platform, and explains the development concept of BP classification algorithm. The source of data mining algorithm supported by cloud computing is discussed. Finally, based on the data mining system of Hadoop cloud platform, this paper designs the corresponding system architecture and data interface, and establishes a suitable testing environment for this system, and completes the simulation experiment test by design. It can be SEEN from the research results that the computation time of this algorithm is directly proportional to the amount of data, and it shows a linear relationship. Compared with the traditional data mining algorithm, the optimized BP algorithm in this paper can significantly save resources in terms of spatial features. This paper designs a kind of optimized operation system based on Hadoop platform through comprehensive analysis of data mining technology and improved algorithm, so as to promote the comprehensive development of data mining technology.