English: This figure presents solution paths when there is a single regressor. The data-optimized OLS parameter equals 2. The ${\displaystyle R^{2}}$ measure of fit is specified to be either 0.5 or 1. In the left panel, an ${\displaystyle \ell _{1}}$ norm is used to penalize deviations from 0 and in the right panel an ${\displaystyle \ell _{2}}$ norm. When ${\displaystyle \lambda }$ values are close to zero, both lines move in the direction of the point (${\displaystyle \lambda =R^{2},\beta =0}$). For the ${\displaystyle \ell _{2}}$ norm, the effect of ${\displaystyle R^{2}}$ diminishes as ${\displaystyle \lambda }$ increases. Based on: Hoornweg, Victor. 2018. Science: Under Submission. Hoornweg Press.