A comparative study of statistical ensemble methods on mismatch conditions

Dingsheng Luo; Ke Chen

A comparative study of statistical ensemble methods on mismatch conditions

Dingsheng Luo, Ke Chen

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Unlike previous comparative studies, we present an empirical evaluation on three typical statistical ensemble methods, boosting [1], bagging [2] and combination of weak perceptrons [3], in terms of speaker identification where miscellaneous mismatch conditions are involved. During creating an ensemble, moreover, different combination strategies are also investigated. As a result, our studies present their generalization capabilities on mismatch conditions, which provides alternative insight to understand those methods.

Original language	English
Title of host publication	Proceedings of the International Joint Conference on Neural Networks\|Proc Int Jt Conf Neural Networks
Publisher	IEEE
Pages	59-64
Number of pages	5
Volume	1
Publication status	Published - 2002
Event	2002 International Joint Conference on Neural Networks (IJCNN '02) - Honolulu, HI Duration: 1 Jul 2002 → …

Conference

Conference	2002 International Joint Conference on Neural Networks (IJCNN '02)
City	Honolulu, HI
Period	1/07/02 → …

Cite this

@inproceedings{8521a7da3d074df893a50c1bb60358c6,

title = "A comparative study of statistical ensemble methods on mismatch conditions",

abstract = "Unlike previous comparative studies, we present an empirical evaluation on three typical statistical ensemble methods, boosting [1], bagging [2] and combination of weak perceptrons [3], in terms of speaker identification where miscellaneous mismatch conditions are involved. During creating an ensemble, moreover, different combination strategies are also investigated. As a result, our studies present their generalization capabilities on mismatch conditions, which provides alternative insight to understand those methods.",

author = "Dingsheng Luo and Ke Chen",

year = "2002",

language = "English",

volume = "1",

pages = "59--64",

booktitle = "Proceedings of the International Joint Conference on Neural Networks|Proc Int Jt Conf Neural Networks",

publisher = "IEEE",

address = "United States",

note = "2002 International Joint Conference on Neural Networks (IJCNN '02) ; Conference date: 01-07-2002",

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TY - GEN

T1 - A comparative study of statistical ensemble methods on mismatch conditions

AU - Luo, Dingsheng

AU - Chen, Ke

PY - 2002

Y1 - 2002

N2 - Unlike previous comparative studies, we present an empirical evaluation on three typical statistical ensemble methods, boosting [1], bagging [2] and combination of weak perceptrons [3], in terms of speaker identification where miscellaneous mismatch conditions are involved. During creating an ensemble, moreover, different combination strategies are also investigated. As a result, our studies present their generalization capabilities on mismatch conditions, which provides alternative insight to understand those methods.

AB - Unlike previous comparative studies, we present an empirical evaluation on three typical statistical ensemble methods, boosting [1], bagging [2] and combination of weak perceptrons [3], in terms of speaker identification where miscellaneous mismatch conditions are involved. During creating an ensemble, moreover, different combination strategies are also investigated. As a result, our studies present their generalization capabilities on mismatch conditions, which provides alternative insight to understand those methods.

M3 - Conference contribution

VL - 1

SP - 59

EP - 64

BT - Proceedings of the International Joint Conference on Neural Networks|Proc Int Jt Conf Neural Networks

PB - IEEE

T2 - 2002 International Joint Conference on Neural Networks (IJCNN '02)

Y2 - 1 July 2002

ER -

A comparative study of statistical ensemble methods on mismatch conditions

Abstract

Conference

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