Twin support vector machineCorrentropy-induced loss functionAlternating iterationHalf-quadratic optimizationAs a variant of the support vector machine (SVM), the twin support vector machine (TSVM) has attracted substantial attention; however, TSVM is sensitive to outliers. To remedy it,this study ...
Robust Fuzzy Least Squares Twin Support Vector Machine for Class Imbalance Learning (RFLSTSVM-CIL)是一种用于处理类别不平衡学习问题的新型机器学习方法。该方法结合了模糊集理论、最小二乘支持向量机和双支持向量机的特点,具有较强的鲁棒性和泛化能力。通过充分利用
In this paper, we present a new type of robust capped L1-norm twin support vector machine with privileged information (R-CTSVM+). Based on the TSVM, the capped L1 norm distance is adopted to reduce abnormal points in the same class which are far from the hyperplane, and the bound of ...
Y. Symmetric LINEX loss twin support vector machine for robust classification and its fast iterative algorithm. Neural Netw. Off. J. Int. Neural Netw. Soc. 168 (2023). Cha, M., Kim, J. S. & Baek, J. G. Density weighted support vector data description. Expert Syst. Appl. 41(7),...
Y. Symmetric LINEX loss twin support vector machine for robust classification and its fast iterative algorithm. Neural Netw. Off. J. Int. Neural Netw. Soc. 168 (2023). Cha, M., Kim, J. S. & Baek, J. G. Density weighted support vector data description. Expert Syst. Appl. 41(7),...
A twin support vector machine (TWSVM) is a classic distance metric learning method for classification problems. The TWSVM criterion is formulated based on the squared L2-norm distance, making it prone to being influenced by the presence of outliers. In this paper, to develop a robust distance...
Recently, there have been several studies utilizing classical machine learning approaches, such as support vector machine (SVM) and RF, and deep learning methods, such as CNN-basic,15,16,38 for outcome prediction or grade classification. To date, several AI methods have been used to assess blas...
In this paper, we propose a robust projection twin support vector machine (RPTSVM), where a new truncated L2 -norm distance measure is applied to the with-class scatter to boost the robustness of the classifier when encountering a large number of outliers. In order to further improve the ...
Least square twin multi-class support vector machine (LST-KSVC) is an efficient algorithm under “one-versus-one-versus-rest” approach. However, it has two drawbacks. One is the use of quadratic loss punishing the rest class samples causes both decision hyperplanes passing through the rest clas...
Weighted quantile regression via support vector machine Expert Systems with Applications (2015)View more references Cited by (13) Robust twin extreme learning machines with correntropy-based metric 2021, Knowledge-Based Systems Show abstract A new heuristic model for monthly streamflow forecasting: Outlier...