Specific Random Trees for Random Forest

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概要

• 論文の詳細を見る

• In this study, a novel forest method based on specific random trees (SRT) was proposed for a multiclass classification problem. The proposed SRT was built on one specific class, which decides whether a sample belongs to a certain class. The forest can make a final decision on classification by ensembling all the specific trees. Compared with the original random forest, our method has higher strength, but lower correlation and upper error bound. The experimental results based on 10 different public datasets demonstrated the efficiency of the proposed method.

• The Institute of Electronics, Information and Communication Engineersの論文

著者

• LIU Zhi

  School of Electrical and Electronic Engineering, Nanyang Technological University

• LIU Zhi

  School of Information Science and Engineering, Shandong University

• SUN Zhaocai

  Department of Computing, Harbin Institute of Technology, Shenzhen Graduate School

• WANG Hongjun

  School of Information Science and Engineering, Shandong University

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• Specific Random Trees for Random Forest
• Specific Random Trees for Random Forest

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