 The choice of loss function here gives rise to several well-known learning algorithms such as regularized least squares and support vector machines.A purely online model in this category would learn based on just the new input formula_18, the current best predictor formula_19 and some extra stored information (which is usually expected to have storage requirements independent of training data size).For many formulations, for example nonlinear kernel methods, true online learning is not possible, though a form of hybrid online learning with recursive algorithms can be used where formula_20 is permitted to depend on formula_21 and all previous data points formula_22.