XploRe Help : rbfinfo

Keywords - Function groups - @ A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

Library:	nn
See also:	rbftest rbfpredict rbfsave rbfload rbftrain rbftrain2

Quantlet:		rbfinfo
Description:		shows information about the given network

Reference(s):

Komorad, K. (2002): On Credit Scoring Estimation, Humbold-University Berlin, unpublished.

Usage:	`rbfinfo(rbfnet)`
Input:
	`rbfnet`	composed object (list), RBF network as computed by rbftrain or rbftrain2

Example:

library("nn") ; load the library ; training set randomize(2020) n = 10 xt = normal(n,2)+#(-1,-1)' | normal(n,2)+#(+1,+1)' yt =(matrix(n)-1)|matrix(n) ; build the RBF network clusters = 2 learn = 0.1|0.2|0.1 epochs = 5|5 mMSE = 0.05 activ = 0 rbfnet = rbftrain(xt,yt,clusters,learn,epochs,mMSE,activ) ; writes down the information rbfinfo(rbfnet)

Result:

Contents of t
[1,] " An  2 - 2 - 1 RBF-network"
[2,] " training epochs: 5 - 5"
[3,] " cluster's learning rates: 0.2000 - 0.1000"
[4,] " output's learning rate: 0.1000"
[5,] " minimum mean squared error: 0.050"
[6,] " BINARY sigmoid activation function"
[7,] " minimum MSE reached: 0.190974 "

Contents of t
[ 1,] " An  2 - 2 - 1 RBF-network"
[ 2,] " training epochs: 5 - 5"
[ 3,] " cluster's learning rates:"
[ 4,] "   0.200"
[ 5,] "   0.175"
[ 6,] "   0.150"
[ 7,] "   0.125"
[ 8,] "   0.100"
[ 9,] " output's learning rate: 0.100"
[10,] " minimum mean squared error: 0.050"
[11,] " BINARY sigmoid activation function"
[12,] "-----------------------------------"
[13,] " Input | Cluster |  Weight   "
[14,] "    1        1      0.784"
[15,] "    1        2      0.332"
[16,] "    2        1      0.740"
[17,] "    2        2      0.367"
[18,] "-----------------------------------"
[19,] " Cluster | Output |  Weight   "
[20,] "    1        1      0.428"
[21,] "    2        1     -0.755"

Author: K. Komorad, 20021212 license MD* Tech