What is the major difference between SVM and Logistic Regression? As both are used for classification purpose and while SVM provides better classification than logistic regression then how is logistic regression advantage over SVM?
While it's true that SVM may come with higher accuracy, LR is much more than just a "classifier" (if we may call it such at all since it predicts a proportion rather than a class). In short, LR is a parametric/probabilistic method, which produces an inferential and highly interpretable statistical model and, on top of interpretability, it may be used in prediction under certain conditions.
On the other hand, SVM is nonparametric and non-interpretable, and it would be useless in a scenario where you'd care to explain the behaviour and interactions of variables rather than just finding patterns for prediction.
That said, while there are many alternatives to the predictive accuracy of SVM, I can't think of many to the inferential power of LR.