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Pattern classification by goal programming and support vector machines

โœ Scribed by Takeshi Asada; Yeboon Yun; Hirotaka Nakayama; Tetsuzo Tanino


Publisher
Springer-Verlag
Year
2004
Tongue
English
Weight
408 KB
Volume
1
Category
Article
ISSN
1619-697X

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Support vector machines for the classifi
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## Abstract The support vector machines (SVMs) method is proposed because it can reflect the sequenceโ€coupling effect for a tetrapeptide in not only a ฮฒโ€turn or nonโ€ฮฒโ€turn, but also in different types of ฮฒโ€turn. The results of the model for 6022 tetrapeptides indicate that the rates of selfโ€consist