Question: Suppose you have trained an SVM classifier with a Gaussian kernel, and it learnedthe following decision boundary on the training set: You suspect that the

Suppose you have trained an SVM classifier with a Gaussian kernel, and it learnedthe following decision boundary on the training set:

Suppose you have trained an SVM classifier with a Gaussian kernel, and

You suspect that the SVM is under fitting your dataset. Should you try increasing or decreasing C? Increasing or decreasing Gamma?

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