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Support-Vector Machines - Why is SVM not popular?
Answer
The Support Vector Machine (SVM) algorithm's lack of effectiveness in specific scenarios has limited its appeal. Typically, SVM is computationally expensive when dealing with big data sets, which diminishes its effectiveness. Since SVM relies on finding a clear boundary between classes, it could struggle to handle datasets that have a lot of noise or overlapping classes.
