Feature selection for least squares projection twin support vector machine

Keyphrases

• Feature Selection 100%
• Projection Twin Support Vector Machine 100%
• Least-squares Projection 100%
• Quadratic Programming 22%
• L1-norm 22%
• Sparse Solution 22%
• Kernel Function 11%
• Selected Features 11%
• Feature Selection Methods 11%
• Regularization Term 11%
• Publicly Available Dataset 11%
• Weight Vector 11%
• Classification Accuracy 11%
• Kernel Trick 11%
• Binary Classification 11%
• Nonlinear Classifier 11%
• Strong Features 11%
• Twin Support Vector Machine (TWSVM) 11%
• Feature Suppression 11%
• Zero Element 11%
• Singularity Problem 11%
• Tikhonov Regularization 11%
• Selection Objective 11%
• Linear Case 11%

Computer Science

• Least Squares Method 100%
• Support Vector Machine 100%
• Feature Selection 100%
• Quadratic Programming 20%
• Sparse Solution 20%
• Kernel Function 10%
• Regularization Term 10%
• Classification Accuracy 10%
• Binary Classification 10%
• Nonzero Element 10%
• Tikhonov Regularization 10%

Mathematics

• Support Vector Machine 100%
• Least Square 100%
• Quadratic Programming 20%
• Programming Problem 20%
• Minimizes 10%
• Regularization 10%
• Nonlinear Case 10%
• Linear Case 10%
• Nonzero Element 10%
• Binary Classification 10%
• Input Feature 10%