Zusammenfassung
We apply an interpreting variant of linear genetic
programming to several diagnosis problems in medicine.
We compare our results to results obtained with neural
networks and argue that genetic programming is able to
show similar performances in classification and
generalization even when using a relatively small
number of generations. Finally, an efficient algorithm
for the elimination of introns in linear genetic
programs is presented
Nutzer