About: ARTOS can be used to quickly learn models for visual object detection without having to collect a set of samples manually. To make this possible, it uses ImageNet, a large image database with more than 20,000 categories. Changes:Initial Announcement on mloss.org.
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About: This package is an implementation of a linear RankSVM solver with non-convex regularization. Changes:Initial Announcement on mloss.org.
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About: LIBLINEAR is a linear classifier for data with millions of instances and features. It supports L2-regularized logistic regression (LR), L2-loss linear SVM, L1-loss linear SVM, and multi-class SVM Changes:Initial Announcement on mloss.org.
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About: BSVM solves support vector machines (SVM) for the solution of large classification and regression problems. It includes three methods Changes:Initial Announcement on mloss.org.
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About: SVMlin: Fast Linear SVMs for Supervised and Semi-supervised Learning Changes:Initial Announcement on mloss.org.
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