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Weighted fusion regularisation and predicting microbial interactions with vector autoregressive model

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成果类型:
期刊论文
作者:
Wang, Yan;He, Tingting*何婷婷);Jiang, Xingpeng(蒋兴鹏);Yuan, Jie;Shen, Xianjun
通讯作者:
He, Tingting
作者机构:
[Wang, Yan] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan 430079, Peoples R China.
[Jiang, Xingpeng; He, Tingting; Shen, Xianjun; Yuan, Jie] Cent China Normal Univ, Sch Comp Sci, Wuhan 430079, Peoples R China.
通讯机构:
[He, Tingting] C
Cent China Normal Univ, Sch Comp Sci, Wuhan 430079, Peoples R China.
语种:
英文
关键词:
microbiome;microbial interactions;vector autoregression model;weighted fusion regularisation;grouping effect
期刊:
International Journal of Data Mining and Bioinformatics
ISSN:
1748-5673
年:
2015
卷:
13
期:
4
页码:
378-394
基金类别:
international cooperation project of Hubei Province [2014BHE0017]; Program of Introducing Talents of Discipline to Universities [B07042]; Major Project of State Language Commission in the Twelfth Five-year Plan Period [ZDI125-1]; Self-determined Research Funds of CCNU from the Colleges' Basic Research and Operation of MOE [CCNU14A02008, CCNU13A05014, CCNU13C01001]
机构署名:
本校为第一且通讯机构
院系归属:
计算机学院
国家数字化学习工程技术研究中心
摘要:
In this paper, we develop a novel regularisation method for MVAR via weighted fusion which considers the correlation among variables. In theory, we discuss the grouping effect of weighted fusion regularisation for linear models. By virtue of the probability method, we show that coefficients corresponding to highly correlated predictors have small differences. A quantitative estimate for such small differences is given regardless of the coefficients signs. The estimate is also improved when consider empirical approximation error if the model fit the data well. We then apply the proposed model o...

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