A multiclass classification method by distance mapping learning network

K. Suzuki; S. Hashimoto

doi:10.1109/ICONIP.2002.1202200

A multiclass classification method by distance mapping learning network

K. Suzuki^*, S. Hashimoto

^*Corresponding author for this work

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

Abstract

We propose a method of multiclass classification by utilizing a distance mapping learning network that is a distance-based multilayer perceptron The network can obtain the non-linear mapping between the input objects and the outputs by providing a pair of objects and the desired distance between them. It thus realizes multiclass classification based on pairwise classifications iteratively. We show the validity of the model with two classification problems: Iris classification and facial expression classification.

Original language	English
Title of host publication	ICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing: Computational Intelligence for the E-Age
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	393-397
Number of pages	5
Volume	1
ISBN (Electronic)	9810475241, 9789810475246
DOIs	https://doi.org/10.1109/ICONIP.2002.1202200
Publication status	Published - 2002
Event	9th International Conference on Neural Information Processing, ICONIP 2002 - Singapore, Singapore Duration: 2002 Nov 18 → 2002 Nov 22

Other

Other	9th International Conference on Neural Information Processing, ICONIP 2002
Country/Territory	Singapore
City	Singapore
Period	02/11/18 → 02/11/22

ASJC Scopus subject areas

Computer Networks and Communications
Information Systems
Signal Processing

Access to Document

10.1109/ICONIP.2002.1202200

Cite this

Suzuki, K., & Hashimoto, S. (2002). A multiclass classification method by distance mapping learning network. In ICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing: Computational Intelligence for the E-Age (Vol. 1, pp. 393-397). [1202200] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICONIP.2002.1202200

A multiclass classification method by distance mapping learning network. / Suzuki, K.; Hashimoto, S.
ICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing: Computational Intelligence for the E-Age. Vol. 1 Institute of Electrical and Electronics Engineers Inc., 2002. p. 393-397 1202200.

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

Suzuki, K & Hashimoto, S 2002, A multiclass classification method by distance mapping learning network. in ICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing: Computational Intelligence for the E-Age. vol. 1, 1202200, Institute of Electrical and Electronics Engineers Inc., pp. 393-397, 9th International Conference on Neural Information Processing, ICONIP 2002, Singapore, Singapore, 02/11/18. https://doi.org/10.1109/ICONIP.2002.1202200

@inproceedings{30f152b63e5642eabad30125122f7cc4,

title = "A multiclass classification method by distance mapping learning network",

abstract = "We propose a method of multiclass classification by utilizing a distance mapping learning network that is a distance-based multilayer perceptron The network can obtain the non-linear mapping between the input objects and the outputs by providing a pair of objects and the desired distance between them. It thus realizes multiclass classification based on pairwise classifications iteratively. We show the validity of the model with two classification problems: Iris classification and facial expression classification.",

author = "K. Suzuki and S. Hashimoto",

year = "2002",

doi = "10.1109/ICONIP.2002.1202200",

language = "English",

volume = "1",

pages = "393--397",

booktitle = "ICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing: Computational Intelligence for the E-Age",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

address = "United States",

note = "9th International Conference on Neural Information Processing, ICONIP 2002 ; Conference date: 18-11-2002 Through 22-11-2002",

}

TY - GEN

T1 - A multiclass classification method by distance mapping learning network

AU - Suzuki, K.

AU - Hashimoto, S.

PY - 2002

Y1 - 2002

N2 - We propose a method of multiclass classification by utilizing a distance mapping learning network that is a distance-based multilayer perceptron The network can obtain the non-linear mapping between the input objects and the outputs by providing a pair of objects and the desired distance between them. It thus realizes multiclass classification based on pairwise classifications iteratively. We show the validity of the model with two classification problems: Iris classification and facial expression classification.

AB - We propose a method of multiclass classification by utilizing a distance mapping learning network that is a distance-based multilayer perceptron The network can obtain the non-linear mapping between the input objects and the outputs by providing a pair of objects and the desired distance between them. It thus realizes multiclass classification based on pairwise classifications iteratively. We show the validity of the model with two classification problems: Iris classification and facial expression classification.

UR - http://www.scopus.com/inward/record.url?scp=84965042620&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84965042620&partnerID=8YFLogxK

U2 - 10.1109/ICONIP.2002.1202200

DO - 10.1109/ICONIP.2002.1202200

M3 - Conference contribution

AN - SCOPUS:84965042620

VL - 1

SP - 393

EP - 397

BT - ICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing: Computational Intelligence for the E-Age

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 9th International Conference on Neural Information Processing, ICONIP 2002

Y2 - 18 November 2002 through 22 November 2002

ER -

A multiclass classification method by distance mapping learning network

Abstract

Other

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this