glmnet

method = 'glmnet'

Type: Regression, Classification

Tuning Parameters: alpha (Mixing Percentage), lambda (Regularization Parameter)

Model Averaged Neural Network

method = 'avNNet'

Type: Classification, Regression

Tuning Parameters: size (#Hidden Units), decay (Weight Decay), bag (Bagging)

Multi-Layer Perceptron

method = 'mlpWeightDecay'

Type: Regression, Classification

Tuning Parameters: size (#Hidden Units), decay (Weight Decay)

Neural Network

method = 'nnet'

Type: Classification, Regression

Tuning Parameters: size (#Hidden Units), decay (Weight Decay)

Neural Networks with Feature Extraction

method = 'pcaNNet'

Type: Classification, Regression

Tuning Parameters: size (#Hidden Units), decay (Weight Decay)

Oblique Random Forest

method = 'ORFridge'

Type: Classification

Tuning Parameters: mtry (#Randomly Selected Predictors)

Penalized Linear Regression

method = 'penalized'

Type: Regression

Tuning Parameters: lambda1 (L1 Penalty), lambda2 (L2 Penalty)

Penalized Logistic Regression

method = 'plr'

Type: Classification

Tuning Parameters: lambda (L2 Penalty), cp (Complexity Parameter)

Penalized Multinomial Regression

method = 'multinom'

Type: Classification

Tuning Parameters: decay (Weight Decay)

Polynomial Kernel Regularized Least Squares

method = 'krlsPoly'

Type: Regression

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

Quantile Regression Neural Network

method = 'qrnn'

Type: Regression

Tuning Parameters: n.hidden (#Hidden Units), penalty ( Weight Decay), bag (Bagged Models?)

Radial Basis Function Kernel Regularized Least Squares

method = 'krlsRadial'

Type: Regression

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

Radial Basis Function Network

method = 'rbf'

Type: Classification

Tuning Parameters: size (#Hidden Units)

Radial Basis Function Network

method = 'rbfDDA'

Type: Regression, Classification

Tuning Parameters: negativeThreshold (Activation Limit for Conflicting Classes)

Relaxed Lasso

method = 'relaxo'

Type: Regression

Tuning Parameters: lambda (Penalty Parameter), phi (Relaxation Parameter)

Ridge Regression

method = 'ridge'

Type: Regression

Tuning Parameters: lambda (Weight Decay)

Ridge Regression with Variable Selection

method = 'foba'

Type: Regression

Tuning Parameters: k (#Variables Retained), lambda (L2 Penalty)