对于稀疏支向量机器的算法

Alfonso Landeros1, Kenneth Lange1,2,3

  • 1Departments of Computational Medicine, University of California, Los Angeles.

Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America
|November 20, 2023
PubMed
概括

这项研究引入了稀疏的约束,作为对分类中变量选择的传统惩罚的替代方案. 这种新的方法可以实现更好的特征稀疏性,而不会影响分类准确性.

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