anchor.diff:                   for vector-error = (learn-vector (first presentation)
                                                     (second presentation)
                                                     net)
  +                 while (not (stop-training net))
                    when (and report-function
                              (or (null (last-report-time net))
                                  (>= (- (get-internal-real-time)
                                         (last-report-time net))
  -                                   time-span-between-reports)))
  +                                   time-span-between-reports))
  +                           error-collection)
                    do
  -                   (let ((mse (if error-collection
  -                                  (/ (apply '+ error-collection)
  -                                     (float (length error-collection)))
  -                                  10.0)))
  +                   (let ((mse (/ (apply '+ error-collection)
  +                                 (float (length error-collection)))))
                        (funcall report-function
                                 :net net
                                 :elapsed (elapsed start-time)
  
positive.code:              :status "learning"
               :elapsed 0
               :iteration 0
               :mse 1.0))
    (when randomize-weights
      (if (listp randomize-weights)
          (apply #'randomize-weights (cons net randomize-weights))
  
negative.code:   (loop for segment in (training-segments net)
         do (delete-file segment)))
  
  (defun tset-to-file 
      (net t-set &optional
                   (filename 
                    (unique-file-name 
                     :extension (format nil ".~a.annt" (id net)))))
    (with-open-file (o filename :direction :output :if-exists :supersede)
      (loop for row in t-set do
           (loop for value across (concatenate 'vector (first row) (second row))
  