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