Annex Testruns: Run No.1

This are the values for training and test:

INP = (Input during training)
0. 0. 0. 1.
1. 0. 0. 1.
0. 1. 0. 0.
1. 1. 0. 0.
0. 0. 1. 1.
0. 1. 1. 1.
1. 0. 1. 0.
1. 1. 1. 0.

TR = (Expected behavior during training)
0. 1.
0. 1.
0. 0.
0. 0.
1. 1.
1. 1.
1. 0.
1. 0.

TST-INP = (Test items)
0. 0. 0. 0.
1. 0. 0. 0.
0. 1. 0. 1.
1. 1. 0. 1.
0. 0. 1. 0.
0. 1. 1. 0.
1. 0. 1. 1.
1. 1. 1. 1.

TST-RESP = (Expected behavior for test items)
0 0.
0. 0
0. 1.
0. 1.
1. 0.
1. 0.
1. 1.
1. 1

th = (threshold values for neurons)
1. 2.

N = (2 neurons for output, the 'hidden layer')

!neuronbin(in,W,th,i) !
!neuronbin(in,W,th,i) !

The elements of the neuron matrix N are stored as strings, but applying the eval()-function to these elements converts the strings in names of working functions which can be used for computations.

The following data have been produced using the scilab-function [i,W,o]=testrun(IN,TST, W,th,N,TR,s).

-->[i,W,o]=testrun(INP,TST, W,th,N,TR,8)
TEST BEFORE LEARNING
NO LEARNINGi=1
 |      0.000 |      0.000 |
i=2
 |      0.000 |      0.000 |
i=3
 |      0.000 |      0.000 |
i=4
 |      0.000 |      0.000 |
i=5
 |      0.000 |      0.000 |
i=6
 |      0.000 |      0.000 |
i=7
 |      0.000 |      0.000 |
i=8
 |      0.000 |      0.000 |
SWITCHING PARTIAL LEARNING AND TESTING
 1 = LEARN------------------------
LEARNINGi=1
TST FOR  1 ------------------------
NO LEARNINGi=1
 |      0.000 |      0.000 |
i=2
 |      0.000 |      0.000 |
i=3
 |      0.000 |      0.000 |
i=4
 |      0.000 |      0.000 |
i=5
 |      0.000 |      0.000 |
i=6
 |      0.000 |      0.000 |
i=7
 |      0.000 |      0.000 |
i=8
 |      0.000 |      0.000 |
 2 = LEARN------------------------
LEARNINGi=1
i=2
TST FOR  2 ------------------------
NO LEARNINGi=1
 |      0.000 |      0.000 |
i=2
 |      0.000 |      0.000 |
i=3
 |      0.000 |      1.000 |
i=4
 |      0.000 |      1.000 |
i=5
 |      0.000 |      0.000 |
i=6
 |      0.000 |      0.000 |
i=7
 |      0.000 |      1.000 |
i=8
 |      0.000 |      1.000 |
 3 = LEARN------------------------
LEARNINGi=1
i=2
i=3
TST FOR  3 ------------------------
NO LEARNINGi=1
 |      0.000 |      0.000 |
i=2
 |      0.000 |      0.000 |
i=3
 |      0.000 |      1.000 |
i=4
 |      0.000 |      1.000 |
i=5
 |      0.000 |      0.000 |
i=6
 |      0.000 |      0.000 |
i=7
 |      0.000 |      1.000 |
i=8
 |      0.000 |      1.000 |
 4 = LEARN------------------------
LEARNINGi=1
i=2
i=3
i=4
TST FOR  4 ------------------------
NO LEARNINGi=1
 |      0.000 |      0.000 |
i=2
 |      0.000 |      0.000 |
i=3
 |      0.000 |      1.000 |
i=4
 |      0.000 |      1.000 |
i=5
 |      0.000 |      0.000 |
i=6
 |      0.000 |      0.000 |
i=7
 |      0.000 |      1.000 |
i=8
 |      0.000 |      1.000 |
 5 = LEARN------------------------
LEARNINGi=1
i=2
i=3
i=4
i=5
TST FOR  5 ------------------------
NO LEARNINGi=1
 |      0.000 |      0.000 |
i=2
 |      0.000 |      0.000 |
i=3
 |      1.000 |      1.000 |
i=4
 |      1.000 |      1.000 |
i=5
 |      1.000 |      0.000 |
i=6
 |      1.000 |      0.000 |
i=7
 |      1.000 |      1.000 |
i=8
 |      1.000 |      1.000 |
 6 = LEARN------------------------
LEARNINGi=1
i=2
i=3
i=4
i=5
i=6
TST FOR  6 ------------------------
NO LEARNINGi=1
 |      0.000 |      0.000 |
i=2
 |      0.000 |      0.000 |
i=3
 |      0.000 |      1.000 |
i=4
 |      0.000 |      1.000 |
i=5
 |      1.000 |      0.000 |
i=6
 |      1.000 |      0.000 |
i=7
 |      1.000 |      1.000 |
i=8
 |      1.000 |      1.000 |
 7 = LEARN------------------------
LEARNINGi=1
i=2
i=3
i=4
i=5
i=6
i=7
TST FOR  7 ------------------------
NO LEARNINGi=1
 |      0.000 |      0.000 |
i=2
 |      0.000 |      0.000 |
i=3
 |      0.000 |      1.000 |
i=4
 |      0.000 |      1.000 |
i=5
 |      1.000 |      0.000 |
i=6
 |      1.000 |      0.000 |
i=7
 |      1.000 |      1.000 |
i=8
 |      1.000 |      1.000 |
 8 = LEARN------------------------
LEARNINGi=1
i=2
i=3
i=4
i=5
i=6
i=7
i=8
TST FOR  8 ------------------------
NO LEARNINGi=1
 |      0.000 |      0.000 |
i=2
 |      0.000 |      0.000 |
i=3
 |      0.000 |      1.000 |
i=4
 |      0.000 |      1.000 |
i=5
 |      1.000 |      0.000 |
i=6
 |      1.000 |      0.000 |
i=7
 |      1.000 |      1.000 |
i=8
 |      1.000 |      1.000 |
 o  =
 
    1.    1.  
 W  =
 
    0.    0.    1.    0.  
    0.    0.    0.    2.  
 i  =
 
    8.
Gerd Doeben-Henisch 2013-01-17