Investigating the Effect of Randomly Selected Feature Subsets on Bagging and Boosting

Author： Wang Guan-Wei   Zhang Chun-Xia   Guo Gao  

Publisher： Taylor & Francis Ltd

ISSN： 0361-0918

Source： Communications in Statistics: Simulation and Computation, Vol.44, Iss.3, 2015-03, pp. : 636-646

Disclaimer: Any content in publications that violate the sovereignty, the constitution or regulations of the PRC is not accepted or approved by CNPIEC.

Previous Menu Next

Related content

Stochastic boosting algorithms

By Jasra Ajay  

Statistics and Computing, Vol. 21, Iss. 3, 2011-07 ,pp. : 335-347

Springer Publishing Company

Access to resources Recommend Favorite

Selection of Binary Variables and Classification by Boosting

By Park Junyong  

Communications in Statistics: Simulation and Computation, Vol. 36, Iss. 4, 2007-07 ,pp. : 855-869

Taylor & Francis Ltd

Access to resources Recommend Favorite

Weighted bagging: a modification of AdaBoost from the perspective of importance sampling

By Yu Qingzhao  

Journal of Applied Statistics, Vol. 38, Iss. 3, 2011-03 ,pp. : 451-463

Taylor & Francis Ltd

Access to resources Recommend Favorite

Kernel density classification and boosting: an L2 analysis

By Marzio M.   Taylor C.  

Statistics and Computing, Vol. 15, Iss. 2, 2005-04 ,pp. : 113-123

Springer Publishing Company

Access to resources Recommend Favorite

AN EM ALGORITHM FOR DENSITY ESTIMATION WITH RANDOMLY CENSORED DATA

By ANDRE ACUSTA   PAUL EGGERMONT   VINCENT LARICCIA  

Journal of Statistical Computation and Simulation, Vol. 73, Iss. 3, 2002-01 ,pp. : 223-232

Taylor & Francis Ltd

Access to resources Recommend Favorite