anchor.diff:   ((testing_samples:List<List<float>>), (teaching_testing_inputs:List<List<float>>))
    =
    let trainOnce = feedForward >> backPropagate
  - let rms network =
  -  (List.map2 (-) network.TargetOutputs network.Outputs)
  -  |> List.map square
  -  |> List.average
  -  |> sqrt
  -  |> (*) 0.5
  +
  + let networkDistance network = distance network.TargetOutputs network.Outputs
   
    match epoch with
    | 0 -> netAcc
  
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: 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 = 1
  
  let trained =
   train
  