Performs either bulk or step-wise hidden node selection.
Usage
hidden_node_sel(
X,
y,
Q,
n_init,
type = "bulk",
inf_crit = "BIC",
task = "regression",
unif = 3,
maxit = 1000,
...
)Arguments
- X
Matrix of covariates
- y
Vector of response
- Q
Candidate number of hidden nodes
- n_init
Number of random initialisations (tracks)
- type
Selection type:
"bulk"(the default) or"step"- inf_crit
Information criterion:
"BIC"(default),"AIC"or"AICc"- task
"regression"(default) or"classification"- unif
Random initial values max value
- maxit
maximum number of iterations for nnet (default = 100)
- ...
additional argument for nnet