Simple and efficient implementation using the kernel trick on concatenated features

Simple and efficient implementation using the kernel trick on concatenated features

krvfl(
  x,
  y,
  lambda = 0.1,
  nb_hidden = 100L,
  activation = c("relu", "sigmoid", "tanh", "linear"),
  sigma = 1,
  seed = NULL,
  ...
)

Arguments

x

Matrix of predictors (n x p)

y

Response vector (n x 1) or matrix (n x m)

lambda

Regularization parameter

nb_hidden

Number of hidden units

activation

Activation function

sigma

Scale parameter for weights

seed

Random seed

...

Additional arguments

Value

krvfl object