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Modified Bagging Applied on Kernel Density Estimator

liuce - Posted on 14 August 2012

Project Description: 

Our project examines the performance and effectiveness of modified bagging when applied to KDE.

Researcher name: 
Stephen M.S. Lee
Researcher position: 
Professor
Researcher department: 
Department of Statistics and Actuarial Science
Researcher email: 
smslee@hku.hk
Researcher name: 
Liu Ce
Researcher position: 
Student Research Assistant
Researcher department: 
School of Economics and Finance
Researcher email: 
williamliu42@gmail.com
Research Project Details
Project Duration: 
03/2012-07/2013
Project Significance: 
Test the validity of Modified Bagging method, provide a better understanding of the limit and potential application of MB method. Provide a way to further improve on the classical KDE, which is expected to be further applied to some more tradition improvement methods.
Results Achieved: 
Research still in progress.
Remarks: 
The project is computationally intensive because of the bootstrap methods involved in modified bagging, and thus my find great value in the application of HPC 2 system.