Estimating complexity of classification tasks using neurocomputers technology

Abstract

This paper presents an alternative approach for estimating task complexity. Construction of a self-organizing neural tree structure, following the paradigm “divide and rule”, requires knowledge about task complexity. Our aim is to determine complexity indicator function and to hallmark its’ main properties. A new approach uses IBM © Zero Instruction Set Computer (ZISC-036 ®) and applies for a range of the different classification tasks.