LIBTwinSVM: A Library for Twin Support Vector Machines
This is an incremental contribution offering a tool for researchers and practitioners working with TSVMs.
The paper introduces LIBTwinSVM, a free and open-source library for Twin Support Vector Machines, providing functionalities like fast estimators and a GUI, with benchmarks showing effectiveness for large-scale classification problems.
This paper presents LIBTwinSVM, a free, efficient, and open source library for Twin Support Vector Machines (TSVMs). Our library provides a set of useful functionalities such as fast TSVMs estimators, model selection, visualization, a graphical user interface (GUI) application, and a Python application programming interface (API). The benchmarks results indicate the effectiveness of the LIBTwinSVM library for large-scale classification problems. The source code of LIBTwinSVM library, installation guide, documentation, and usage examples are available at https://github.com/mir-am/LIBTwinSVM.