Gaussian Process with Polynomial Kernel
method = 'gaussprPoly'
Type: Regression, Classification
Tuning Parameters: degree (Polynomial Degree), scale (Scale)
Least Squares Support Vector Machine with Polynomial Kernel
method = 'lssvmPoly'
Type: Classification
Tuning Parameters: degree (Polynomial Degree), scale (Scale)
Penalized Discriminant Analysis
method = 'pda'
Type: Classification
Tuning Parameters: lambda (Shrinkage Penalty Coefficient)
Penalized Discriminant Analysis
method = 'pda2'
Type: Classification
Tuning Parameters: df (Degrees of Freedom)
Polynomial Kernel Regularized Least Squares
method = 'krlsPoly'
Type: Regression
Tuning Parameters: lambda (Regularization Parameter), degree (Polynomial Degree)
Quadratic Discriminant Analysis
method = 'qda'
Type: Classification
No Tuning Parameters
Quadratic Discriminant Analysis with Stepwise Feature Selection
method = 'stepQDA'
Type: Classification
Tuning Parameters: maxvar (Maximum #Variables), direction (Search Direction)
Regularized Discriminant Analysis
method = 'rda'
Type: Classification
Tuning Parameters: gamma (Gamma), lambda (Lambda)
Relevance Vector Machines with Polynomial Kernel
method = 'rvmPoly'
Type: Regression
Tuning Parameters: scale (Scale), degree (Polynomial Degree)
Robust Quadratic Discriminant Analysis
method = 'QdaCov'
Type: Classification
No Tuning Parameters
Stepwise Diagonal Quadratic Discriminant Analysis
method = 'sddaQDA'
Type: Classification
No Tuning Parameters
Support Vector Machines with Polynomial Kernel
method = 'svmPoly'
Type: Regression, Classification
Tuning Parameters: degree (Polynomial Degree), scale (Cost), C (Scale)