  Crossover and mutation are the two main operators that lead to new solutions
in evolutionary approaches. In this article, a new method of performing the
crossover phase is presented. The problem of choice is evolutionary decision
tree construction. The method aims at finding such individuals that together
complement each other. Hence we say that they are diversely specialized. We
propose the way of calculating the so-called complementary fitness. In several
empirical experiments, we evaluate the efficacy of the method proposed in four
variants and compare it to a fitness-rank-based approach. One variant emerges
clearly as the best approach, whereas the remaining ones are below the
baseline.
