pnn.imp: Derive the importance rank of all predictors used in the PNN

In yap: Yet Another Probabilistic Neural Network

Description

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

Usage

pnn.imp(net)

Arguments

net	A PNN object generated by pnn.fit()

Value

A dataframe with important values of all predictors in the PNN

See Also

pnn.x_imp

Examples

data(iris, package = "datasets")
Y <- iris[, 5]
X <- scale(iris[, 1:4])
pnet <- pnn.fit(x = X, y = Y)

pnn.imp(pnet)

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