青岛科技大学主页平台管理系统 wangminghui--Home-- SGL-SVM: A novel method for tumor classification via support vector machine with sparse group Lasso

Personal Information

Qingdao University of Science and Technology

王明辉

Paper Publications

Current position: Home / Scientific Research / Paper Publications

SGL-SVM: A novel method for tumor classification via support vector machine with sparse group Lasso

Key Words:Tumor classification; Gene expression data; Feature selection; Sparse group Lasso; Support vector machine
Abstract:
Volume:486
Issue:
Translation or Not:no

Pre One:M2D-QPCA: An Improved Quaternion Principal Component Analysis Method for Color Face Recognition

Next One:Iterative Methods for Least Squares Problem in Split Quaternionic Mechanics