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.