p202fig05.16 In the simplest example of category learning, the category that receives the largest total input from the feature level is chosen, and drives learning in the adaptive weights that abut it.  Learning in this "classifying vector", denoted by zi, makes this vector more parallel to the input vector from the feature level that is driving the learning (dashed red arrow).<BR>||  Geometry of choice and learning