首页|Studies Conducted at Soochow University on Computational Intelligence Recently R eported (Sparse Learning-based Feature Selection In Classification: a Multi-obje ctive Perspective)
Studies Conducted at Soochow University on Computational Intelligence Recently R eported (Sparse Learning-based Feature Selection In Classification: a Multi-obje ctive Perspective)
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
Data detailed on Machine Learning-Co mputational Intelligence have been presented. According to news reporting origin ating from Suzhou, People's Republic of China, by NewsRx correspondents, researc h stated, "Sparse learning-based feature selection is an emerging topic, acclaim ed for its potential in delivering promising performance and interpretability. N evertheless, the task of determining a suitable regularization parameter to stri ke a balance between the loss function and regularization is a challenging endea vor, where existing methods encounter great difficulties." Financial supporters for this research include National Natural Science Foundati on of China (NSFC), Marsden Fund (NZ), Science for Technological Innovation Chal lenge (SfTI), New Zealand Ministry of Business, Innovation and Employment (MBIE) , NZ-SQ Data Science Catalyst Program, Fundamental Research Funds for the Centra l Universities, JLU, Guangdong Science and Technology Strategic Innovation Fund.
SuzhouPeople's Republic of ChinaAsiaComputational IntelligenceMachine LearningSoochow University
NETL
NSTL
