A fuzzy support vector machine with qualitative regression preset

Yicheng Wei; Junzo Watada; Witold Pedrycz

doi:10.1109/ICGEC.2012.15

A fuzzy support vector machine with qualitative regression preset

Yicheng Wei^*, Junzo Watada, Witold Pedrycz

^*この研究の対応する著者

研究成果: Conference contribution

6 被引用数 (Scopus)

抄録

In this paper, we formulate a qualitative classification model by means of qualitative fuzzy regression presetbased fuzzy support vector machine (FQR-FSVM). This new model will make it possible to achieve discrimination of output while characterizing membership for each class in terms of multi-dimensional qualitative inputs (attributes). Moreover, the new model will largely shorten the computing time especially for large database by using linear preset of fuzzy qualitative regression classifier to limit the non-linear classification region.

本文言語	English
ホスト出版物のタイトル	Proceedings - 2012 6th International Conference on Genetic and Evolutionary Computing, ICGEC 2012
ページ	393-399
ページ数	7
DOI	https://doi.org/10.1109/ICGEC.2012.15
出版ステータス	Published - 2012
イベント	2012 6th International Conference on Genetic and Evolutionary Computing, ICGEC 2012 - Kitakyushu 継続期間: 2012 8月 25 → 2012 8月 28

Other

Other	2012 6th International Conference on Genetic and Evolutionary Computing, ICGEC 2012
City	Kitakyushu
Period	12/8/25 → 12/8/28

ASJC Scopus subject areas

生化学、遺伝学、分子生物学（全般）

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10.1109/ICGEC.2012.15

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Wei, Y, Watada, J & Pedrycz, W 2012, A fuzzy support vector machine with qualitative regression preset. in Proceedings - 2012 6th International Conference on Genetic and Evolutionary Computing, ICGEC 2012., 6457100, pp. 393-399, 2012 6th International Conference on Genetic and Evolutionary Computing, ICGEC 2012, Kitakyushu, 12/8/25. https://doi.org/10.1109/ICGEC.2012.15

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title = "A fuzzy support vector machine with qualitative regression preset",

abstract = "In this paper, we formulate a qualitative classification model by means of qualitative fuzzy regression presetbased fuzzy support vector machine (FQR-FSVM). This new model will make it possible to achieve discrimination of output while characterizing membership for each class in terms of multi-dimensional qualitative inputs (attributes). Moreover, the new model will largely shorten the computing time especially for large database by using linear preset of fuzzy qualitative regression classifier to limit the non-linear classification region.",

keywords = "Fuzzy qualitative regression classifier, Fuzzy support vector machine (FSVM), Qualitative classification",

author = "Yicheng Wei and Junzo Watada and Witold Pedrycz",

year = "2012",

doi = "10.1109/ICGEC.2012.15",

language = "English",

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pages = "393--399",

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note = "2012 6th International Conference on Genetic and Evolutionary Computing, ICGEC 2012 ; Conference date: 25-08-2012 Through 28-08-2012",

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AU - Watada, Junzo

AU - Pedrycz, Witold

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AB - In this paper, we formulate a qualitative classification model by means of qualitative fuzzy regression presetbased fuzzy support vector machine (FQR-FSVM). This new model will make it possible to achieve discrimination of output while characterizing membership for each class in terms of multi-dimensional qualitative inputs (attributes). Moreover, the new model will largely shorten the computing time especially for large database by using linear preset of fuzzy qualitative regression classifier to limit the non-linear classification region.

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BT - Proceedings - 2012 6th International Conference on Genetic and Evolutionary Computing, ICGEC 2012

T2 - 2012 6th International Conference on Genetic and Evolutionary Computing, ICGEC 2012

Y2 - 25 August 2012 through 28 August 2012

ER -

A fuzzy support vector machine with qualitative regression preset

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