grnn.optmiz_auc: Optimize the optimal value of GRNN smoothing parameter based...
In yager: Yet Another General Regression Neural Network

Description Usage Arguments Value See Also Examples

The function grnn.optmiz_auc optimize the optimal value of GRNN smoothing parameter by cross-validation. It is applicable to the classification.

1	grnn.optmiz_auc(net, lower = 0, upper, nfolds = 4, seed = 1, method = 1)

`net`	A GRNN object generated by grnn.fit()
`lower`	A scalar for the lower bound of the smoothing parameter
`upper`	A scalar for the upper bound of the smoothing parameter
`nfolds`	A scalar for the number of n-fold, 4 by default
`seed`	The seed value for the n-fold cross-validation, 1 by default
`method`	A scalar referring to the optimization method, 1 for Golden section searc and 2 for Brent’s method

The best outcome

grnn.search_auc

data(iris, package = "datasets")
Y <- ifelse(iris[, 5] == "setosa", 1, 0)
X <- scale(iris[, 1:4])
gnet <- grnn.fit(x = X, y = Y)
## Not run: 
grnn.optmiz_auc(net = gnet, lower = 3, upper = 7, nfolds = 2)

## End(Not run)