Iris data classification by means of pseudo neural networks based on evolutionary symbolic regression

Abstract

This research deals with a novel approach to classification. Iris data was used for the experiments. Classical artificial neural networks, where a relation between inputs and outputs is based on the mathematical transfer functions and optimized numerical weights, was an inspiration for this work. Artificial neural networks need to optimize weights, but the structure and transfer functions are usually set up before the training. The proposed method utilizes the symbolic regression for synthesis of a whole structure, i.e. the relation between inputs and output(s) and tested on iris data in this case. For experimentation, Differential Evolution (DE) for the main procedure and also for meta-evolution version of analytic programming (AP) was used.