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A Data Mining Algorithm based on Relevant Vector Machine of Cloud Simulation

Volume 14, Number 6, June 2018, pp. 1360-1364
DOI: 10.23940/ijpe.18.06.p28.13601364

Wuqi Gaoa,Gang Lib, and Hui Liuc

aSchool of Computer Science and Technology, Xi’an Technological University, Xi’an, 710021, China
bSchool of Economics and Management, Xi’an Technological University, Xi’an, 710021, China
cSchool of Electronics and Information Engineering, Xi’an Technological University, Xi’an, 710021, China

(Submitted on March 29, 2018; Revised on April 12, 2018; Accepted on May 23, 2018)

Abstract:

Regarding the problems of long time running and memory overflowing caused from the analysis of data mining algorithms for tactical communication network simulation data, using relevance vector machine (RVM), a data mining algorithm that is mainly used on the small sample of data mining with a good effect but a large amount of calculation that is based on an open source distributed storage and computing platform Hadoop, the author designs a kind of relevance vector machine data mining algorithm based on cloud computing. Based on the sum of the distribution of small sample data mining law in sequence, in some cases, the algorithm reflects the law of large sample data mining. Then, it carries on programming and empirical research, which supports the analysis of massive cloud simulation data.

 

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