# 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 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)