grnn.fit: Create a general regression neural network

In yager: Yet Another General Regression Neural Network

Description

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

Usage

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

Arguments

x	The matrix of predictors
y	The vector of response variable
sigma	The scalar of smoothing parameter
w	The vector of weights with default = 1 for each record

Value

A general regression neural network object

References

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

Examples

data(iris, package = "datasets")
Y <- ifelse(iris[, 5] == "setosa", 1, 0)
X <- scale(iris[, 1:4])
gnet <- grnn.fit(x = X, y = Y)

Example output

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