Which of the following algorithm(s) requires fitting a linear model multiple times? Forward selection that terminates upon selecting one feature (m 1) Lasso with cross-validation Lasso with a fixed value of the regularization parameter = Backward selection that terminates upon selecting one feature (m = 1)

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A: GIVEN: