anchor.diff:    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)
  -//  train
  -//   ((-) epoch 1)
  -//   trained
  -//   (training_samples, teaching_inputs)
  -//   (testing_samples, teaching_testing_inputs)
  -/// end train f.
   
   
   
  
positive.code:     | a::b, c::d -> vecOp (*) xs ys |> List.sum
      | _, _ -> acc 
  
  let rec shuffleList count (sysRand:System.Random) (xs:List<'a>) =
   match count with
   | 0 -> xs
  
negative.code: let rec dataAtIndex  xs_data xs_index =
   match xs_index with
   | [] -> []
   | hd::tl -> (List.item hd xs_data)::(dataAtIndex xs_data tl)
  
  let rec f1 mapper x ys = List.map (mapper x) ys
  let rec f2 mapper xs ys = //***normalize
   match xs with
   | [] -> []
   | hd::tl -> (f1 mapper hd ys)::(f2 mapper tl ys)
  
  let square x = x * x
  let sclarVectorMul x ys = f1 (*) x ys
  let mulVectors xs ys    = List.map2 (*) xs ys
  let addVectors xs ys    = List.map2 (+) xs ys
  