grnn.imp: Derive the importance rank of all predictors used in the GRNN

In yager: Yet Another General Regression Neural Network

Description

The function grnn.imp derives the importance rank of all predictors used in the GRNN It essentially is a wrapper around the function grnn.x_imp.

Usage

grnn.imp(net, class = FALSE)

Arguments

net	The GRNN object generated by grnn.fit()
class	TRUE or FALSE, whether it is for the classification or not

Value

A dataframe with important values of all predictors in the GRNN

See Also

grnn.x_imp

Examples

data(iris, package = "datasets")
Y <- ifelse(iris[, 5] == "setosa", 1, 0)
X <- scale(iris[, 1:3])
gnet <- grnn.fit(x = X, y = Y)
## Not run: 
grnn.imp(net = gnet, class = TRUE)

## End(Not run)

yager documentation built on Oct. 26, 2020, 1:06 a.m.