Gaussian Process

method = 'gaussprLinear'

Type: Regression, Classification

No Tuning Parameters

Gaussian Process with Polynomial Kernel

method = 'gaussprPoly'

Type: Regression, Classification

Tuning Parameters: degree (Polynomial Degree), scale (Scale)

Gaussian Process with Radial Basis Function Kernel

method = 'gaussprRadial'

Type: Regression, Classification

Tuning Parameters: sigma (Sigma)

Least Squares Support Vector Machine

method = 'lssvmLinear'

Type: Classification

No Tuning Parameters

Least Squares Support Vector Machine with Polynomial Kernel

method = 'lssvmPoly'

Type: Classification

Tuning Parameters: degree (Polynomial Degree), scale (Scale)

Least Squares Support Vector Machine with Radial Basis Function Kernel

method = 'lssvmRadial'

Type: Classification

Tuning Parameters: sigma (Sigma)

Oblique Random Forest

method = 'ORFsvm'

Type: Classification

Tuning Parameters: mtry (#Randomly Selected Predictors)

Partial Least Squares

method = 'kernelpls'

Type: Regression, Classification

Tuning Parameters: ncomp (#Components)

Polynomial Kernel Regularized Least Squares

method = 'krlsPoly'

Type: Regression

Tuning Parameters: lambda (Regularization Parameter), degree (Polynomial Degree)

Radial Basis Function Kernel Regularized Least Squares

method = 'krlsRadial'

Type: Regression

Tuning Parameters: lambda (Regularization Parameter), sigma (Sigma)

Relevance Vector Machines with Linear Kernel

method = 'rvmLinear'

Type: Regression

No Tuning Parameters

Relevance Vector Machines with Polynomial Kernel

method = 'rvmPoly'

Type: Regression

Tuning Parameters: scale (Scale), degree (Polynomial Degree)

Relevance Vector Machines with Radial Basis Function Kernel

method = 'rvmRadial'

Type: Regression

Tuning Parameters: sigma (Sigma)

Support Vector Machines with Class Weights

method = 'svmRadialWeights'

Type: Classification

Tuning Parameters: sigma (Sigma), C (Cost), Weight (Weight)

Support Vector Machines with Linear Kernel

method = 'svmLinear'

Type: Regression, Classification

Tuning Parameters: C (Cost)

Support Vector Machines with Polynomial Kernel

method = 'svmPoly'

Type: Regression, Classification

Tuning Parameters: degree (Polynomial Degree), scale (Cost), C (Scale)

Support Vector Machines with Radial Basis Function Kernel

method = 'svmRadial'

Type: Regression, Classification

Tuning Parameters: sigma (Sigma), C (Cost)

Support Vector Machines with Radial Basis Function Kernel

method = 'svmRadialCost'

Type: Regression, Classification

Tuning Parameters: C (Cost)