anchor.diff:  
   let square x = x * x
   
  +let distance xs ys =
  +  (List.map2 (-) xs ys)
  +  |> List.map square
  +  |> List.average
  +  |> sqrt
  +  |> (*) 0.5
  +
  +/// Euclid Norm.
   let rec norm xs =
    let rec f xs acc =
     match xs with
  
positive.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 = 10000
  
  let trained =
   train
  
negative.code:   let errTresholdMeet = (rms_trained_err < best_trained_err) && (rms_validated_err < best_test_err)
    if errTresholdMeet then trained
    else train ((-) epoch 1) trained (training_samples, teaching_inputs) (testing_samples, teaching_testing_inputs)
  
  
  let inputSize = 7;
  