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Neuron Net Configuration:
 1) Type of Neural Network 
   a) Number of Neurons
   b) Number of Connections
   c) All Connections, In, Out Functions
 2) Minor & Major Quality Functions
 3) Wizard - Some standart types of Neural Networks
   a) Preceptron
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Data File Configuration:
 1) File with TEST Data samples
     a) Name
     b) Number of Lines
 2) File with CONTROL Data samples
     a) Name
     b) Number of Lines
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Text Output / Debug Configuration:
 1) File for text(debug) output
 2) Debug Level
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Neural Network initialisation Config
 1) Method of generating start weights
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Neural Network Producing Config
 1) Maximum Number of NNetworks alive in one time
 2) Start number of NNetworks
 3) Number of childs to be produced
 4) Weights of Randomaze/Corelate/Combine
   and some specific oprions
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Droping equal Config
 1)  Mechanism to prevent presenting in current NNetworks set 
   some equal or similliar members.
     It based on determinig maximal & sumar weight diference.
   and if diference is less when specified in this Config part
   then member with worse quality will be droped.
 2)  You may want to have some fixed percentes of new (or old) 
    members in current NNetwork set. Here options to make it
 3)  You may want to fixate some weights ( they may be found
    from other algoritm or you think they don't have major 
    relation on Network Output ) then you may here protect
    them from changing.
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Graphical Output
 1) Size of Output screen
 2) Number Iteration's in one graphical step
 3) Some other related options
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AutoSetup Configuration
 1) Number of iterations to finish    
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