Computer Science ›› 2018, Vol. 45 ›› Issue (11A): 121-125.

• Intelligent Computing • Previous Articles     Next Articles

Research and Application of Ensemble Learning Using Gradient Optimization Decision Tree

WANG Yan-bin, WU You-xi, LIU Hong-pu   

  1. School of Artificial Intelligence,Hebei University of Technology,Tianjin 300401,China
    Hebei Province Key Laboratory of Big Data Calculation,Tianjin 300401,China
  • Online:2019-02-26 Published:2019-02-26

Abstract: Ensemble learning completes the learning task by building multiple classifiers with certain complementary performance to reduce the classification error.However,the current research fails to consider the local validity of the classifier.In this paper,a hierarchical multi-class classification algorithm was proposed in the framework of ensemble learning.The algorithm decomposes the problem by predicted category,and integrates several weak classifiers on the basis of stratification to improve the prediction accuracy.The experimental results on a real data set of American College Matriculation Set and three UCI datasets verified the effectiveness of the algorithm.

Key words: Classifier fusion, Ensemble learning, Gradient optimization, Hierarchical structure

CLC Number: 

  • TP181
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