A classification model based on neural tree ensemble is presented for the characteristics of classification in
data mining, which establishes a single neural tree model by using modified genetic programming and particle swarm
optimization for its optimization. Then more neural tree models are combined to form the final classification model by
the idea of ensemble learning. Experimental results show that this model is effective for the classification, and especially for
the complex classification with multi-class attributes.