yager (version 0.1.0)

grnn.fit: Create a general regression neural network

Description

The function grnn.fit creates a general regression neural network (GRNN)

Usage

grnn.fit(x, y, w = rep(1, length(y)), sigma = 1)

Arguments

x

The matrix of predictors

y

The vector of response variable

w

The vector of weights with default = 1 for each record

sigma

The scalar of smoothing parameter

Value

A general regression neural network object

References

Donald Specht. (1991). A General Regression Neural Network.

Examples

# NOT RUN {
data(iris, package = "datasets")
Y <- ifelse(iris[, 5] == "setosa", 1, 0)
X <- scale(iris[, 1:4])
gnet <- grnn.fit(x = X, y = Y)
# }