Linganisha mbinu

	Mashine ya Vektor Saidizi ya Mtandaoni	Usajili wa Usajili wa Mtandaoni
Nyanja	Ujifunzaji wa Mashine	Ujifunzaji wa Mashine
Familia	Machine learning	Machine learning
Mwaka wa asili	2005–2011	1960s (perceptron); formalized for logistic loss ~2000s
Mwanzilishi	Shalev-Shwartz, Singer, et al. (Pegasos); Bordes, Bottou et al. (LASVM)	Rosenblatt, F. / Widrow, B. (perceptron era); modern SGD form: Bottou, L.
Aina	Online kernel classifier	Incremental supervised classifier
Chanzo asilia	Shalev-Shwartz, S., Singer, Y., Srebro, N., & Cotter, A. (2011). Pegasos: Primal estimated sub-gradient solver for SVM. Mathematical Programming, 127(1), 3–30.	Bottou, L. (2010). Large-Scale Machine Learning with Stochastic Gradient Descent. In Proceedings of COMPSTAT 2010, 177–186. Physica-Verlag.
Majina mbadala	Online SVM, Incremental SVM, LASVM, Pegasos SVM	incremental logistic regression, streaming logistic regression, SGD logistic classifier, online binary classifier
Zinazohusiana	3	5
Muhtasari	Online SVM adapts the classical support vector machine to streaming or sequentially arriving data by updating the decision boundary one example at a time rather than solving a global quadratic program. Algorithms such as Pegasos and LASVM make this tractable at large scale, preserving the margin-maximising spirit of SVMs with sub-linear time per update.	Online Logistic Regression fits a logistic classifier one sample (or mini-batch) at a time via stochastic gradient descent, updating model weights as each observation arrives rather than waiting to see the full dataset. This makes it the standard choice for high-volume, streaming, or memory-constrained binary classification problems where batch training is infeasible.