yager (version 0.1.0)

grnn.x_pfi: Derive the permutation feature importance of a predictor used in the GRNN

Description

The function grnn.x_pfi derives the permutation feature importance (PFI) of a predictor used in the GRNN

Usage

grnn.x_pfi(net, i, class = FALSE, ntry = 1000, seed = 1)

Arguments

net

The GRNN object generated by grnn.fit()

i

The ith predictor in the GRNN

class

TRUE or FALSE, whether it is for the classification or not

ntry

The number of random permutations to try, 1e3 times by default

seed

The seed value for the random permutation

Value

A vector with the variable name and the PFI value.

See Also

grnn.x_imp

Examples

# NOT RUN {
data(iris, package = "datasets")
Y <- ifelse(iris[, 5] == "setosa", 1, 0)
X <- scale(iris[, 1:4])
gnet <- grnn.fit(x = X, y = Y)
grnn.x_pfi(net = gnet, 1)
# }