liquidSVM: A Fast and Versatile SVM package. liquidSVM is a package written in C++ that provides SVM-type solvers for various classification and regression tasks. Because of a fully integrated hyper-parameter selection, very carefully implemented solvers, multi-threading and GPU support, and several built-in data decomposition strategies it provides unprecedented speed for small training sizes as well as for data sets of tens of millions of samples. Besides the C++ API and a command line interface, bindings to R, MATLAB, Java, Python, and Spark are available. We present a brief description of the package and report experimental comparisons to other SVM packages.
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References in zbMATH (referenced in 3 articles )
Showing results 1 to 3 of 3.
- Guerra, Maria Letizia; Sorini, Laerte; Stefanini, Luciano: Quantile and expectile smoothing based on (L_1)-norm and (L_2)-norm fuzzy transforms (2019)
- Farooq, Muhammad; Steinwart, Ingo: An SVM-like approach for expectile regression (2017)
- Ingo Steinwart, Philipp Thomann: liquidSVM: A Fast and Versatile SVM package (2017) arXiv