abstract = "a method for classification of two types of objects
using genetic programming (GP) has been presented.
These two objects are coins of different sizes, and
different textures. The basic algorithm of genetic
programming was presented and explained. The features
used for training and testing are mean, standard
deviation, skewness and kurtosis. Precision and recall
were used as performance measures and they were the
main building blocks in building the fitness function.
They replaced the false alarm and detection rate that
was used in previous works. The result figures as well
as values of precision, recall, fitness values, time
elapsed, and number of generations used in training was
presented. The very basic structure of a GP system was
implemented and proved that it can work well as a
standalone computational algorithm.",