Question: ssume a data set consists only of a single data point {(x, 1)}. How many times would the Perceptron algorithm mis-classify this point x before

ssume a data set consists only of a single data point {(x, 1)}. How many times would the Perceptron algorithm mis-classify this point x before convergence? What if the initial weight vector w0 was initialized randomly and not as the all-zero vector

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