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)

• Links

  train Model List

• Topics

  • Data Sets
  • Visualizations
  • Pre-Processing
  • Data Splitting
  • Miscellaneous Model Functions
  • Model Training and Tuning
  • train Model List
  • train Models By Tag
  • train Models By Similarity
  • Using Custom Models
  • Variable Importance
  • Feature Selection
  • Other Functions
  • Parallel Processing