Linear SVM has learning rate , Value of penalty denoted by C . These are hyperparameter and need to be tested with values to increase accuracy
True or False? Linear SVMs have no hyperparameters that need to be set by cross-validation
Hey @chiragwxN, by linear svm in the question, the question mean that the data which is completely linearly separable, meaning there are no outliers present, and so there is no need to introduce error term, and hence C =0 or better assume that c is not present.
Happy Lerning 
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