LIBLINEAR is a linear classifier for data with millions of instances and features. It supports L2-regularized logistic regression (LR), L2-loss linear SVM, and L1-loss linear SVM.
Main features of LIBLINEAR include
* Same data format as LIBSVM, our general-purpose SVM solver, and also similar usage
* Multi-class classification: 1) one-vs-the rest, 2) Crammer & Singer
* Cross validation for model selection
* Probability estimates (logistic regression only)
* Weights for unbalanced data
* MATLAB/Octave, Java interfaces
Implementation and demo of explainable coding of clinical notes with Hierarchical Label-wise Attention Networks (HLAN) - acadTags/Explainable-Automated-Medical-Coding
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J. Wehrmann, R. Cerri, and R. Barros. Proceedings of the 35th International Conference on Machine Learning, volume 80 of Proceedings of Machine Learning Research, page 5075--5084. Stockholmsmässan, Stockholm Sweden, PMLR, (10--15 Jul 2018)
H. Dong, V. Suárez-Paniagua, W. Whiteley, and H. Wu. (2020)cite arxiv:2010.15728Comment: Structured abstract in full text, 17 pages, 5 figures, 4 supplementary materials (3 extra pages), submitted to Journal of Biomedical Informatics.