anchor.diff:                      ((= layer-index output-layer-index) :output)
                       (t :hidden))
                 :neuron-count (elt (topology net) layer-index)
  -              :transfer-tag 
  -              (if (= layer-index (1- (length (topology net))))
  -                  :none
  -                  (transfer-tag net))
  +              :transfer-tag (transfer-tag net)
                 :net net)))
     (loop for layer in (layers net)
        for next-layer = (if (eql (layer-type layer) :output)
  
positive.code:    (layer-type :accessor layer-type :initarg :layer-type :initform nil)
     (biased :reader biased :initarg :biased :initform nil :type boolean)
     (id :accessor id :type integer)
     (input :accessor input :initform 0.0 :type real)
     (transfer-tag :accessor transfer-tag :initarg :transfer-tag :initform :sigmoid)
     (transfer-function :accessor transfer-function :initform nil)
  
negative.code:          for c = (sqrt (+ (* x x) (* y y)))
           collect (list (vector x y) (vector (if (> c diameter) 0 1))))))
       
  (defun xor-training ()
    (list (list #(0.0 0.0) #(1.0))
          (list #(0.0 1.0) #(0.0))
          (list #(1.0 0.0) #(0.0))
          (list #(1.0 1.0) #(1.0))))
  