.png){kind=icon}
返回
Enhanced automatic twin support vector machine for imbalanced data classification
.png){kind=icon}
PRE
AI
DOI：10.1016/j.patcog.2020.107442.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Most of the classification approaches assume that the sample distribution among classes is balanced. Still, such an assumption leads to biased performance over the majority class. This paper proposes an enhanced automatic twin support vector machine - (EATWSVM) to deal with imbalanced data, which incorporates a kernel representation within a TWSVM-based optimization. To learn the kernel function, we impose a Gaussian similarity, ruled by a Mahalanobis distance, and couple a centered kernel alignment-based approach to improving the data separability. Besides, we suggest a suitable range to fix the regularization parameters concerning both the dataset' imbalance ratio and overlap. Lastly, we adopt One-vs-One and One-vs-Rest frameworks to extend our EATWSVM formulation for multi-class tasks. Obtained results on synthetic and real-world datasets show that our approach outperforms state-of-the-art methods concerning classification performance and training time. (C) 2020 Elsevier Ltd. All rights reserved.
Keyword:
Imbalanced data
Kernel methods
Twin support vector machines
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
7.6
论文数:
1.3W
被引数:
4.5W
机构
引用论文
Maximum Margin of Twin Spheres Support Vector Machine for Imbalanced Data Classification用于不平衡数据分类的双球支持向量机最大间隔
PREAI
分享收藏KNN-based maximum margin and minimum volume hyper-sphere machine for imbalanced data classification
PREAI
分享收藏An efficient weighted Lagrangian twin support vector machine for imbalanced data classification一种有效的加权拉格朗日孪生支持向量机，用于不平衡数据分类.png)
PATTERN RECOGNITION
PATTERN RECOGNITIONIF7.6
PREAI
分享收藏A robust fuzzy least squares twin support vector machine for class imbalance learning用于类不平衡学习的鲁棒模糊最小二乘孪生支持向量机
PREAI
分享收藏Study of the impact of resarnpling methods for contrast pattern based classifiers in imbalanced databases研究不平衡数据库中基于对比度模式的分类器的重新采样方法的影响NEUROCOMPUTING
NEUROCOMPUTINGIF6.5
PREAI
分享收藏
查看更多内容