标题:Specific Random Trees for Random Forest
作者:Zhi LIU;Zhaocai SUN;Hongjun WANG
作者机构:[Liu, Z] School of Information Science and Engineering, Shandong University, Jinan, China;[ Sun, Z] Department of Computing, Harbin Institute of Techn 更多
通讯作者地址:[Liu, Z]Shandong Univ, Sch Informat Sci & Engn, Jinan 250100, Peoples R China.
来源:IEICE transactions on information and systems
出版年:2013
卷:E96D
期:3
页码:739-741
DOI:10.1587/transinf.E96.D.739
关键词:random forest;multiclass classification;specific random trees
摘要: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.
收录类别:EI;SCOPUS;SCIE
Scopus被引频次:1
资源类型:期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84878215936&doi=10.1587%2ftransinf.E96.D.739&partnerID=40&md5=a81c22f36df6b9c27b1c5add2d9749f2
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