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actually shrink some of the coefficients to zero, thus reducing both variance and model complexity. Lasso uses a technique called soft-thresholding[1]. It shrinks each coefficient by a constant amount such that, when the coefficient value is lower than the shrinkage constant it’s reduced to zero.