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Can non-linearly separable data always be made linearly separable?
A data set that is linearly separable is a precondition for algorithms like the perceptron to converge. It's well-known that we can project low-dimensional data to a higher dimension using kernel ...
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2
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1
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Is the decision boundary of voted/average perceptron linear like basic perceptron?
Is the decision boundary of voted/average perceptron linear like basic perceptron? How can you justify that?
It's related to solve binary classification problems in Machine Learning context.
