首页|Study Findings from National University of Defense Technology Broaden Understand ing of Support Vector Machines (Multi-Output Bayesian Support Vector Regression Considering Dependent Outputs)
Study Findings from National University of Defense Technology Broaden Understand ing of Support Vector Machines (Multi-Output Bayesian Support Vector Regression Considering Dependent Outputs)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
Investigators publish new report on . According to news reporting originating from Changsha, People's Republic of Chin a, by NewsRx correspondents, research stated, "Multi-output regression aims to u tilize the correlation between outputs to achieve information transfer between d ependent outputs, thus improving the accuracy of predictive models." Financial supporters for this research include National Natural Science Foundati on of China. The news correspondents obtained a quote from the research from National Univers ity of Defense Technology: "Although the Bayesian support vector machine (BSVR) can provide both the mean and the predicted variance distribution of the data to be labeled, which has a large potential application value, its standard form is unable to handle multiple outputs at the same time. To solve this problem, this paper proposes a multi-output Bayesian support vector machine model (MBSVR), wh ich uses a covariance matrix to describe the relationship between outputs and ou tputs and outputs and inputs simultaneously by introducing a semiparametric late nt factor model (SLFM) in BSVR, realizing knowledge transfer between outputs and improving the accuracy of the model."
National University of Defense Technolog yChangshaPeople's Republic of ChinaAsiaEmerging TechnologiesMachine Le arningSupport Vector MachinesSupport Vector RegressionVector Machines
NETL
NSTL
