Transcription of LIBLINEAR: A Library for Large Linear Classi cation
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Journal of Machine Learning Research 9 (2008) 1871-1874 Submitted 5/08; Published 8/08 LIBLINEAR: A Library for Large Linear ClassificationRong-En of Computer ScienceNational Taiwan UniversityTaipei 106, TaiwanLast modified: March 5, 2022 Editor:Soeren SonnenburgAbstractLIBLINEARis an open source Library for Large -scale Linear classification. It supports logisticregression and Linear support vector machines. We provide easy-to-use command-line toolsand Library calls for users and developers. Comprehensive documents are available for bothbeginners and advanced users. Experiments demonstrate thatLIBLINEARis very efficienton Large sparse data : Large -scale Linear classification, logistic regression, support vector machines,open source, machine learning1.
Linear classi cation has become one of the most promising learning techniques for large sparse data with a huge number of instances and features. We develop LIBLINEAR as an easy-to-use tool to deal with such data. It supports L2-regularized logistic regression (LR), L2-loss and L1-loss linear support vector machines (SVMs) (Boser et al., 1992). It
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