Implementation of Bayesian high dimensional data analysis with SIR model program

Kun Xia

doi:10.1117/12.2642856

28 July 2022 Implementation of Bayesian high dimensional data analysis with SIR model program

Kun Xia

Proceedings Volume 12303, International Conference on Cloud Computing, Internet of Things, and Computer Applications (CICA 2022); 123030A (2022) https://doi.org/10.1117/12.2642856
Event: International Conference on Cloud Computing, Internet of Things, and Computer Applications, 2022, Luoyang, China

Abstract

In order to solve the problem of large mean square error of regression coefficient in traditional Bayesian high-dimensional data analysis, sir model program is applied to realize Bayesian high dimensional data analysis. This paper capture Bayesian high dimensional data, and use sir model program to set super parameters. The prior probability of Bayesian high dimensional data analysis is calculated, and the topological structure of Bayesian high dimensional data analysis is constructed to realize Bayesian high dimensional data analysis. The results show that the mean square error of regression coefficient in the experimental group is significantly lower than that in the control group, which can solve the problem of large mean square error in traditional analysis.

Citation Download Citation

Kun Xia "Implementation of Bayesian high dimensional data analysis with SIR model program", Proc. SPIE 12303, International Conference on Cloud Computing, Internet of Things, and Computer Applications (CICA 2022), 123030A (28 July 2022); https://doi.org/10.1117/12.2642856

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