Computer Science ›› 2018, Vol. 45 ›› Issue (4): 157-162.doi: 10.11896/j.issn.1002-137X.2018.04.026

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Intranet Defense Algorithm Based on Pseudo Boosting Decision Tree

LI Bai-shen, LI Ling-zhi, SUN Yong and ZHU Yan-qin   

  • Online:2018-04-15 Published:2018-05-11

Abstract: Combining with the idea of TF-IDF algorithm,the frequency of characteristics(Eigen Frequency),the frequency of forest(Forest Frequency) and the pseudo boosting decision tree(PBDT) were put forward,solving the margi-nalized problem of wrong data with the increasing number of iterations for gradient boosting decision tree(GBDT).In PBDT,all the decision trees produce respectively in data sets after the original data set of the Bootstrapping,without aiming at each iteration to sample data sets.Then intranet defense experiment was conducted on distributed cluster.The experimental results show that on the training set with a certain scale,PBDT has better prediction accuracy.

Key words: Pseudo boosting decision tree,Distributed cluster,Intranet defense

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