ThunderSVM: A Fast SVM Library on GPUs and CPUs
November 26, 2019 ยท View on GitHub
The mission of ThunderSVM is to help users easily and efficiently apply SVMs to solve problems. ThunderSVM exploits GPUs and multi-core CPUs to achieve high efficiency. Key features of ThunderSVM are as follows.
- Support all functionalities of LibSVM such as one-class SVMs, SVC, SVR and probabilistic SVMs.
- Use same command line options as LibSVM.
- Support Python, R and Matlab interfaces.
- Supported Operating Systems: Linux, Windows and MacOS.
Why accelerate SVMs: A survey conducted by Kaggle in 2017 shows that 26% of the data mining and machine learning practitioners are users of SVMs.
