| Library: | nn |
| See also: | nnrnet ann nnrpredict nnrload |
| Quantlet: | nnrsave | |
| Description: | saves a network into a file with a given name |
| Usage: | nnrsave(net, name) | |
| Input: | ||
| net | list, composed object from nnrnet | |
| name | string, name of a file (without extension) | |
| Output: | ||
| output files | 6 files ("name"+"ext", "ext" being one of ".nng", ".nnn", ".nnc", ".nno" and ".nnw") containing the information about the net | |
library("nn")
x = read("kredit")
t = read("tkredit")
y = x[,1]
x = x[,2:21]
x =(x-min(x))./(max(x)-min(x))
net = nnrnet(x, y, matrix(rows(x)), 10)
nnrsave(net, "nnkred")
runs a neural network with 10 hidden units for the kredit data of Fahrmeier and Hammerled, computes the predicted values and saves them in the files nnkred.xxx Contents of ts [1,] "A 20 - 10 - 1 network:" [2,] "# weights : 221" [3,] "linear output : no" [4,] "error function: least squares" [5,] "log prob model: no" [6,] "skip links : no" [7,] "max. weight : 0.70" [8,] "decay : 0" [9,] "max. Iterat : 100"