Many authors of papers I read affirm SVMs is superior technique to face their regression/classification problem, aware that they couldn't get similar results through NNs. Often the comparison states that SVMs, instead of NNs, Have a strong founding theory Reach the global optimum due to quadratic programming Have no issue for choosing a proper number of parameters Are less prone to overfitting Nee
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