xor.net

一个关于人工智能-神经网络的例子及其算法程序

[TRAINING]  QUICKPROP	%training method
[MINWEIGHTS]  -10	%minimum weight value
[MAXWEIGHTS]  10	%maximum weight value
[PERTURBATION] 5	%maximum weight perturbation
[SATURATION] 80		%saturation threshold
[PREVSAT] 0		%prevent saturation flag
[PLOTMEM] 0		%plot memorization flag
[PATTERNCLIP] 0.01	%Learned pattern clipping
[TOLERANCE] 0.001	%solution tolerance
[GAIN] 0.1		%learning gain
[MOMENTUM] 0		%learning momentum
[ERRORMARGIN] 0.1	%classification error margin
[RPROPWTINC] 1.2	%RPROP Weight increase
[RPROPWTDEC] 0.5	%RPROP Weight decrease
[RPROPWTMAX] 50	%RPROP Max Weight change
[RPROPWTMIN] 1e-06		%RPROP Min Weight change
[RPROPINIWT] 0.001	%RPROP Initial Weight change
[QUICKPROPMU] 1.75	%QuickProp Max Weight change
[DBDWTINC] 0.06		%DBD Weight increase
[DBDWTDEC] 0.2		%DBD Weight decrease
[DBDAVERAGE] 0.7	%RPROP Weight increase
[EPOCHS] 10000		%max # of training cycles
[LAYERS] 3		%total number of layers
[LAYERDATA] 2 2 1 	%# of neurons in each layer
[TRAININGFILE] Xor.trn
[WEIGHTSFILE] xor.wts
[TESTFILE] Xor.tst