Neuronomator

Neural network backpropagation alghoritm implementation.

Building

Enter source root and build jar

./gradlew jar

Then run

java -jar build/libs/neuronomator-v*.jar

Where '*' is current version number.

Example output

:: Neuronomator 6000 ::

-----[Menu]--------------------------------------------------------------------------
1. Enter network parameters
2. Use example parameter set
0. Exit
>1
Enter neuron values of input layer (space separated numbers)
>0.1 0.5 -1.1
Enter expected neuron values of output layer
>1 0.5
Enter number of hidden layers
>3
Enter amount of neurons in hidden layers
>5

         |o| |o| |o|          
| 0.100| |o| |o| |o|          
| 0.500| |o| |o| |o| | 1.000| 
|-1.100| |o| |o| |o| | 0.500| 
         |o| |o| |o|          

Ok? [y/n]>y
Enter maximum number of iterations
>10000
Enter tolerated error value
>0.001
-----[Learning]----------------------------------------------------------------------
Iteration 120/10000 : error = 0.000997
Total error within limit: 0.000997 < 0.001000
-----[Calculated weights]------------------------------------------------------------
L1-L2
	N1:  0.900301527199445  0.338078030425155  0.894659920727425  0.808234182152787  0.509193591540590 
	N2:  0.435294619497994  0.164606087790771  0.053671849125107  0.658242733174273  0.951942727415133 
	N3:  0.209925662362869  0.592757088887489  0.153404466804703  0.685278864578829  0.001779232116602 
L2-L3
	N1:  0.697843709393024  0.443407312865462  0.386151950005018  0.037194289531313  0.559474308554924 
	N2:  0.459147565346800  0.825132033730962  0.969622855532442  0.203889209859832  0.657990549792086 
	N3:  0.925243051574435  0.174001367618224  0.055413026985691  0.128605962952163  0.694110619626155 
	N4:  0.143744302016388  0.860644999496252  0.203079853817374  0.747446793810407  0.732982561784035 
	N5:  0.884614386880747  0.721942872043656  0.074790634223207  0.848910016017671  0.585737527958521 
L3-L4
	N1:  0.384611369631635  0.542452644288881  0.912731374405039  0.157770701677564  0.163577706751285 
	N2:  0.555455487684515  0.440466530418831  0.792419379920480  0.289957765502128  0.975146744655604 
	N3:  0.504084019085070  0.632725412149788  0.434352748240295  0.511020974542947  0.446470797469131 
	N4:  0.636095304544909  0.945417373300297  0.653745192801613  0.106415080842864  0.630196828410803 
	N5:  0.017637606925763  0.761403063029708  0.026501561707617  0.699380182677549  0.580809787153521 
L4-L5
	N1:  0.873277463215451  0.105045263889206 
	N2:  0.240665176531862  0.280888830309884 
	N3:  1.007541148420476  0.263975751836411 
	N4:  0.943221339467878 -0.099218291084971 
	N5:  0.510657990692959 -0.564422705777302