Computer Science ›› 2021, Vol. 48 ›› Issue (11): 184-191.doi: 10.11896/jsjkx.200900107

• Database & Big Data & Data Science • Previous Articles     Next Articles

Imbalanced Data Classification of AdaBoostv Algorithm Based on Optimum Margin

LU Shu-xia1,2, ZHANG Zhen-lian1   

  1. 1 College of Mathematics and Information Science,Hebei University,Baoding,Hebei 071002,China
    2 Hebei Province Key Laboratory of Machine Learning and Computational Intelligence,Baoding,Hebei 071002,China
  • Received:2020-09-11 Revised:2021-02-06 Online:2021-11-15 Published:2021-11-10
  • About author:LU Shu-xia,born in 1966,Ph.D,professor,postgraduate supervisor,is a member of China Computer Federation.Her main research interests include machine learning and so on.
  • Supported by:
    National Natural Science Foundation of China(61672205) and Key R & D Program of Science and Technology Foundation of Hebei Province(19210310D).

Abstract: In order to solve the problem of imbalanced data classification,this paper proposes an AdaBoostv algorithm based on optimal margin.In this algorithm,the improved SVM is used as the base classifier,the margin mean term is introduced into the optimization model of SVM,and the margin mean term and loss function term are weighted by data imbalance ratio.The stochastic variance reduced gradient (SVRG) is used to solve the optimization model to improve the convergence rate.In the optimal margin AdaBoostv algorithm,a new adaptive cost sensitive function is introduced into the instance weight update formula,the minority instances,the misclassified instances and the borderline minority instances are assigned higher cost values.In addition,a new weight strategy of the base classifier is derived by combining the new weight formula and introducing the estimated value of the optimal margin under the given precision parameter v,so as to further improve the classification accuracy of the algorithm.The experimental results show that the classification accuracy of the AdaBoostv algorithm with optimal margin is better than other algorithms on imbalanced datasets in the case of linear and nonlinear,and it can obtain a larger minimum margin.

Key words: AdaBoostv, Adaptive cost sensitive function, Imbalanced data, Optimum margin, SVRG

CLC Number: 

  • TP181
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