Comparison of sparse least squares support vector regressors trained in primal and dual.
Shigeo AbePublished in: ESANN (2008)
Keyphrases
- least squares
- support vector
- svm classifier
- sparse linear
- ls svm
- linear regression
- dual formulation
- primal dual
- regression problems
- algorithm for linear programming
- high dimensional
- optical flow
- classification accuracy
- feature selection
- simplex algorithm
- radial basis function
- cross validation
- support vector machine
- generalization ability
- kernel function
- canonical correlation analysis
- training set
- loss function
- convex optimization
- hyperparameters
- reduced set
- image classification
- lower bound