pnn.predone: Calculate the predicted probability for each category of PNN
In yap: Yet Another Probabilistic Neural Network

Description Usage Arguments Value See Also Examples

View source: R/pnn.predone.R View source: R/pnn.predonev1.R

The function pnn.predone calculates the predicted probability for each category of PNN

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pnn.predone(net, x)

pnn.predone(net, x)

`net`	A PNN object created by pnn.fit()
`x`	A vector of input predictors

A one-row matrix of predicted probabilities

pnn.fit

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