logl: Calculate the multiclass cross-entropy

In yap: Yet Another Probabilistic Neural Network

Description

The function logl calculates the multiclass cross entropy

Usage

logl(y_true, y_pred)

Arguments

y_true	A matrix of multiclass 0/1 indicators
y_pred	A matrix of predicted probability of each class

Value

The value of multiclass cross entropy

Examples

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

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