Genetic Programming (GP) is a field under the hood of Evolutionary
Computing, that has been successful in addressing a variety of
problems in the field of data mining and machine learning,
notexcluding the problems of multi-class classification
(mcc). However, its realms have been successful only in extending the
binary GP classifiers to the problems of mcc, thereof still retaining
a void of not having any efficient multi-class classifiers, when
compared to non-GP classifiers. In this work, I will present a novel
algorithm that incorporates some ideas on the representation of the
solution space for a tree based GP, that will lay some foundations on
filling this void, which might also lead to some future research in
this direction. During the presentation, I shall reveal the success
and competitiveness of this approach, and discuss about the future
directions.