In SVM, RBF kernel with appropriate parameters to perform binary classification where the data is non-linearly seperable. In this scenario

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the decision boundry in the transformed feature space in linear

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the decision boundry in the transformed feature space in non-linear

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the decision boundry in the original feature space in not considered

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the decision boundry in the original feature space in linear

Q. In SVM, RBF kernel with appropriate parameters to perform binary classification where the data is non-linearly seperable. In this scenario