Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
385684 | Expert Systems with Applications | 2011 | 6 Pages |
Abstract
In this paper, a new weighted approach on Lagrangian support vector machine for imbalanced data classification problem is proposed. The weight parameters are embedded in the Lagrangian SVM formulation. The training method for weighted Lagrangian SVM is presented and its convergence is proven. The weighted Lagrangian SVM classifier is tested and compared with some other SVMs using synthetic and real data to show its effectiveness and feasibility.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Jae Pil Hwang, Seongkeun Park, Euntai Kim,