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:                                    (string-downcase (id net))))
  
          (training-segments net) (make-training-segments tset max-segment-size)
          (max-mse net) -1000000.0
          (min-mse net) 1000000.0
          (last-anneal-iteration net) 0
          (anneal net) nil
          (randomize net) nil
  
negative.code:              :status "learning"
               :elapsed 0
               :iteration 0
               :mse (min-mse net)))
    (when randomize-weights
      (if (listp randomize-weights)
          (apply #'randomize-weights (cons net randomize-weights))
  