Hybrid flexible neural tree approach for leukemia cancer classification

In this paper, a novel method for improving flexible neural tree is proposed to classify the leukemia cancer data. The hybrid flexible neural tree with pre-defined instruction sets can be created and evolved. The structure and parameter of hybrid flexible neural tree are optimized using probabilistic incremental program evolution (PIPE) and particle swarm optimization (PSO) algorithm. The experimental results indicate that the proposed method illustrates feasible and efficient for the classifications of microarray data.