Yet another Example

Let us assume we have a data set with outputs/targets given by the vector

$$\boldsymbol{y}=\begin{bmatrix}4 \\ 2 \\3\end{bmatrix},$$

and our inputs as a $3\times 2$ design matrix

$$\boldsymbol{X}=\begin{bmatrix}2 & 0\\ 0 & 1 \\ 0 & 0\end{bmatrix},$$

meaning that we have two features and two unknown parameters $\beta_0$ and $\beta_1$ to be determined either by ordinary least squares, Ridge or Lasso regression.

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