Solving the Optimal Solution of Weight Vectors on GP-Decision Tree

In this paper, a novel approach based on genetic programming algorithm (GPA) is proposed to solve the optimal solution of weight vectors on GP-decision tree. In this GP-decision tree algorithm, the GP-decision tree is constructed according to the error rate of tree nodes and the error rate reduction of partitioned nodes. By using this algorithm, not only the weight vectors of tree nodes can be solved, but also the structure of GP-decision tree can be determined. Experimental results show this algorithm is efficient and the right trend forecasting model can be selected by using this GP-decision tree algorithm.