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Svm - What are the disadvantages of SVM?
Answer
Drawbacks of SVM Training on big datasets takes a long time. The outcome model, variable weights, and individual effects are all murky and hard to make sense of. We are unable to make minor adjustments to the model due to the final model's lack of transparency, making it difficult to integrate our business logic.
