pnn.parpred: Calculate predicted probabilities of PNN by using parallelism

In yap: Yet Another Probabilistic Neural Network

Description

The function pnn.parpred calculates a matrix of PNN predicted probabilities based on an input matrix

Usage

pnn.parpred(net, x)

Arguments

net	A PNN object generated by pnn.fit()
x	A matrix of input predictors

Value

A matrix of predicted probabilities

See Also

pnn.predict

Examples

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

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