NL repository
menu
검색
Library
Browse
Communities & Collections
By Date
Authors
Titles
Subject
My Repository
My Account
Receive email updates
Edit Profile
DSpace at EWHA
자연과학대학
통계학전공
Journal papers
View : 678 Download: 0
Bias corrections for Random Forest in regression using residual rotation
Title
Bias corrections for Random Forest in regression using residual rotation
Authors
Song
;
J.
Ewha Authors
송종우
SCOPUS Author ID
송종우
Issue Date
2015
Journal Title
Journal of the Korean Statistical Society
ISSN
1226-3192
Citation
Journal of the Korean Statistical Society vol. 44, no. 2, pp. 321 - 326
Keywords
Bias correction
;
Random Forest
;
Regression
Publisher
Korean Statistical Society
Indexed
SCIE; SCOPUS; KCI
Document Type
Article
Abstract
This paper studies bias correction methods for Random Forest in regression. Random Forest is a special bagging trees that can be used in regression and classification. It is a popular method because of its high prediction accuracy. However, we find that Random Forest can have significant bias in regression at times. We propose a method to reduce the bias of Random Forest in regression using residual rotation. The real data applications show that our method can reduce the bias of Random Forest significantly. © 2015 The Korean Statistical Society.
DOI
10.1016/j.jkss.2015.01.003
Appears in Collections:
자연과학대학
>
통계학전공
>
Journal papers
Files in This Item:
There are no files associated with this item.
Export
RIS (EndNote)
XLS (Excel)
XML
Show full item record
Find@EWHA
트윗하기
BROWSE
Communities & Collections
By Date
Authors
Titles
Subject