Skip navigation
Skip navigation

Boosting through optimization of margin distributions

Shen, Chunhua; Li, Hanxi

Description

Boosting has been of great interest recently in the machine learning community because of the impressive performance for classifi- cation and regression problems. The success of boosting algorithms may be interpreted in terms of the margin theory. Recently, it has been shown that generalization error of classifiers can be obtained by explicitly taking the margin distribution of the training data into account. Most of the current boosting algorithms in practice usually optimize a convex loss...[Show more]

CollectionsANU Research Publications
Date published: 2010
Type: Journal article
URI: http://hdl.handle.net/1885/64748
Source: IEEE Transactions on Neural Networks
DOI: 10.1109/TNN.2010.2040484

Download

File Description SizeFormat Image
01_Shen_Boosting_through_optimization_2010.pdf531.07 kBAdobe PDF    Request a copy


Items in Open Research are protected by copyright, with all rights reserved, unless otherwise indicated.

Updated:  20 July 2017/ Responsible Officer:  University Librarian/ Page Contact:  Library Systems & Web Coordinator