Extension of Incremental Linear Discriminant Analysis to Online Feature Extraction under Nonstationary Environments
In this paper, a new approach to an online feature extraction under nonstationary environments is proposed by extending Incremental Linear Discriminant Analysis (ILDA). The extended ILDA not only detect so-called “concept drifts” but also transfer the knowledge on discriminant feature spaces of the...
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Springer-Verlag Berlin Heidelberg
2012
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オンライン・アクセス: | http://ir.unimas.my/id/eprint/17807/1/Extension%20of%20Incremental%20Linear%20Discriminant%20%28abstract%29.pdf http://ir.unimas.my/id/eprint/17807/ https://link.springer.com/chapter/10.1007/978-3-642-34481-7_78 |
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my.unimas.ir.178072017-09-27T07:06:54Z http://ir.unimas.my/id/eprint/17807/ Extension of Incremental Linear Discriminant Analysis to Online Feature Extraction under Nonstationary Environments Joseph, A. Jang, Young-Min Ozawa, Seiichi Lee, Minho T Technology (General) In this paper, a new approach to an online feature extraction under nonstationary environments is proposed by extending Incremental Linear Discriminant Analysis (ILDA). The extended ILDA not only detect so-called “concept drifts” but also transfer the knowledge on discriminant feature spaces of the past concepts to construct good feature spaces. The performance of the extended ILDA is evaluated for the benchmark datasets including sudden changes and reoccurrence in concepts. Springer-Verlag Berlin Heidelberg 2012 E-Article PeerReviewed text en http://ir.unimas.my/id/eprint/17807/1/Extension%20of%20Incremental%20Linear%20Discriminant%20%28abstract%29.pdf Joseph, A. and Jang, Young-Min and Ozawa, Seiichi and Lee, Minho (2012) Extension of Incremental Linear Discriminant Analysis to Online Feature Extraction under Nonstationary Environments. International Conference on Neural Information Processing. pp. 640-647. ISSN 978-3-642-34487-9 (ISBN) https://link.springer.com/chapter/10.1007/978-3-642-34481-7_78 |
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T Technology (General) Joseph, A. Jang, Young-Min Ozawa, Seiichi Lee, Minho Extension of Incremental Linear Discriminant Analysis to Online Feature Extraction under Nonstationary Environments |
description |
In this paper, a new approach to an online feature extraction under nonstationary environments is proposed by extending Incremental Linear Discriminant Analysis (ILDA). The extended ILDA not only detect so-called “concept drifts” but also transfer the knowledge on discriminant feature spaces of the past concepts to construct good feature spaces. The performance of the extended ILDA is evaluated for the benchmark datasets including sudden changes and reoccurrence in concepts. |
format |
E-Article |
author |
Joseph, A. Jang, Young-Min Ozawa, Seiichi Lee, Minho |
author_facet |
Joseph, A. Jang, Young-Min Ozawa, Seiichi Lee, Minho |
author_sort |
Joseph, A. |
title |
Extension of Incremental Linear Discriminant Analysis to Online Feature Extraction under Nonstationary Environments |
title_short |
Extension of Incremental Linear Discriminant Analysis to Online Feature Extraction under Nonstationary Environments |
title_full |
Extension of Incremental Linear Discriminant Analysis to Online Feature Extraction under Nonstationary Environments |
title_fullStr |
Extension of Incremental Linear Discriminant Analysis to Online Feature Extraction under Nonstationary Environments |
title_full_unstemmed |
Extension of Incremental Linear Discriminant Analysis to Online Feature Extraction under Nonstationary Environments |
title_sort |
extension of incremental linear discriminant analysis to online feature extraction under nonstationary environments |
publisher |
Springer-Verlag Berlin Heidelberg |
publishDate |
2012 |
url |
http://ir.unimas.my/id/eprint/17807/1/Extension%20of%20Incremental%20Linear%20Discriminant%20%28abstract%29.pdf http://ir.unimas.my/id/eprint/17807/ https://link.springer.com/chapter/10.1007/978-3-642-34481-7_78 |
_version_ |
1644512714002792448 |
score |
13.250246 |