liquidSVM
PublicSupport vector machines (SVMs) and related kernel-based learning algorithms are a well-known class of machine learning algorithms, for non-parametric classification and regression. liquidSVM is an implementation of SVMs whose key features are: fully integrated hyper-parameter selection, extreme speed on both small and large data sets, full flexibility for experts, and inclusion of a variety of different learning scenarios: multi-class classification, ROC, and Neyman-Pearson learning, and least-squares, quantile, and expectile regression.
apache-sparkc-plus-plusclassificationexpectile-regressionmachine-learningmatlabmloctavepythonquantile-regression
Creat：2017-04-23T06:16:26
Update：2025-01-21T20:26:10
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