基于ELM的改进CART决策树回归算法

为提高CART(ClassificationAndRegressionTree)决策树回归算法的准确性,提出一种基于ELM(Extreme Learning Machine)的改进CART决策树回归算法——ELM-CART算法.所提算法主要是在CART回归树创建过程中,在每个叶节点使用极限学习机建模,可以得到真正意义上...

Improved CART Decision Tree Regression Algorithm Based on ELM

In order to increase the accuracy of the Classification And Regression Tree (CART) regression algorithm, we propose an improved CART regression algorithm based on Extreme Learning Machine (ELM-CART for short). The proposed algorithm mainly applies the ELM for modeling at each leaf node in the process of creating a CART, which can get the true regression prediction value, improve the generalization ability, and compensate for such disadvantages of the CART regression algorithm as easy overfitting and constant predictive output. The experimental results show that the proposed algorithm can effectively improve the prediction accuracy of target data in regression analysis, and its accuracy is higher than that of the counterparts.