Biased support vector machine and weighted-smote in handling class imbalance problem

Biased support vector machine and weighted-smote in handling class imbalance problem

Class imbalance occurs when instances in a class are much higher than in other classes. This machine learning major problem can affect the predicted accuracy. Support Vector Machine (SVM) is robust and precise method in handling class imbalance problem but weak in the bias data distribution, Biased...

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Bibliographic Details
Main Authors: Hartono Hartono, Opim Salim Sitompul, Tulus Tulus, Erna Budhiarti Nababan
Format: Article
Language:English
Published: Universitas Ahmad Dahlan 2018-03-01
Series:IJAIN (International Journal of Advances in Intelligent Informatics)
Subjects:
Class Imbalance
Biased Support Vector Machine
Borderline-SMOTE
Positive Samples
Negative Samples
Online Access:http://ijain.org/index.php/IJAIN/article/view/146

Internet

http://ijain.org/index.php/IJAIN/article/view/146

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