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Classias is a collection of machine-learning algorithms for
classification. Currently, it supports the following formalizations:
L1/L2-regularized logistic regression (aka. Maximum Entropy)
L1/L2-regularized L1-loss linear-kernel Support Vector Machine (SVM)
Averaged perceptron
It implements several algorithms for training classifiers:
Averaged perceptron
Limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) [Nocedal80]
Orthant-Wise Limited-memory Quasi-Newton (OWL-QN) [Andrew07]
Primal Estimated sub-GrAdient SOlver (Pegasos) [Shalev-Shwartz07]
Truncated Gradient [Langford09], also known as FOrward LOoking
Subgradient (FOLOS) [Duchi09] specialized for L1 regularization
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