anchor.diff:  let testing_samples = [| [ 0.692; 0.000; 0.000; 0.174; 0.000; 0.000; 0.000; ] |]
   let teaching_samples_inputs = [| [ 1.0; 0.0; 0.0; 0.0; 0.0; 0.0; 0.0; 0.0; 0.0; 0.0; 1.0; 0.0; 0.0;  ] |]
   
  -let epoch = 10000
  +let epoch = 1
   
   let trained =
    train
  
positive.code:   let shuffled_testing_i = dataAtIndex teaching_testing_inputs testing_rand_index
  
    let trained = List.fold2 (funcNet trainOnce) netAcc shuffled_training_s shuffled_training_i
    let rms_trained_err = rms trained
  
    let validated = List.fold2 (funcNet feedForward) netAcc shuffled_testing_s shuffled_testing_i
    let rms_validated_err = rms validated
  
  //  if epoch % 100 = 0 then printfn "%f %f" rms_trained_err rms_validated_err
    printfn "%f %f" rms_trained_err rms_validated_err
  
negative.code:  ((testing_samples:List<List<float>>), (teaching_testing_inputs:List<List<float>>))
   =
   let trainOnce = feedForward >> backPropagate
  
   let networkDistance network = distance network.TargetOutputs network.Outputs
  
   match epoch with
   | 0 -> netAcc
  