Optimized bio-inspired kernels with twin support vector machine using low identity sequences to solve imbalance multiclass classification

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Optimized bio-inspired kernels with twin support vector machine using low identity sequences to solve imbalance multiclass classification

The function of enzymes is performed differently depending on their bio-chemical mechanisms and important to the prediction of protein structure and function. In order to overcome the weaknesses of imbalance data distribution in subclasses prediction we proposed Bio-Twin Support Vector Machine (Bio–...

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Bibliographic Details
Main Authors:	Guramand, S.K., Saedudin, R.D.R., Hassan, R., Kasim, S., Ramlan, R., Salim, B. W.
Format:	Article
Language:	English
Published:	Triveni Enterprises, Lucknow (India) 2019
Subjects:	QH Natural history T Technology (General)
Online Access:	http://eprints.uthm.edu.my/4626/ http://eprints.uthm.edu.my/4626/1/AJ%202019%20%28299%29.pdf

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