Keyphrases
Center Vector
33%
Covariance Matrix
66%
Forward Selection
33%
Generalized Kernel
100%
Kernel Models
100%
Kernel Regressor
33%
Lagrange Dual Problem
33%
Learning Input
33%
Least Squares Support Vector Regression (LSSVR)
100%
Loss Function
33%
Lunate
33%
Model Weight
33%
Modeling Approach
33%
Orthogonal Forward Selection
100%
Orthogonal Least Squares
33%
Regression Modeling
66%
Regression Problem
33%
Regression-based Method
100%
Regressor
100%
Regressor Selection
33%
Reproducing Kernel Hilbert Space
33%
Selection Strategy
33%
Sparse Regression
33%
Sparse Representation
33%
Weight Parameter
33%
Computer Science
Diagonal Covariance Matrix
100%
Dual Problem
50%
Forward Selection
100%
Hilbert Space
50%
Insensitive Loss
50%
Least Squares Method
50%
Real Data Sets
50%
regression modeling
100%
Regression Problem
50%
Reproducing Kernel
50%
Sparse Representation
50%
Structure Model
50%
Support Vector Regression
100%
Mathematics
Covariance Matrix
40%
Diagonal
40%
Dual Problem
20%
Hilbert Space
20%
Least Squares Method
20%
Loss Function
20%
Model Structure
20%
Modeling Approach
20%
Real Data
20%
Regressors
100%
Sparse Matrix
20%
Support Vector Machine
100%
Engineering
Covariance Matrix
40%
Decomposition Concept
20%
Lagrange
20%
Least Squares Method
20%
Loss Function
20%
Model Structure
20%
Real Data
20%
Regressors
100%
Reproducing Kernel Hilbert Space
20%
Selection Procedure
20%
Support Vector Machine
100%