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"