$Los{s}_h(z)=\{\begin{array}{ccc}0& if& z1\\ 1-z,& \text{o}\text{t}\text{h}\text{e}\text{r}\text{w}\text{i}\text{s}\text{e}& \end{array}$

In this problem, we calculate the empirical risk with hinge loss when given specific $$ and $\{(x^{(t)},y^{(t)}){\}}_t=1,$dots,$n.$ Assume we have $4$ training examples $($i$.$e$.n=4),$ where $x^{(t)}in{R}^3$ and $y^{(t)}$ is a scalar. The training examples $\{(x^{(t)},y^{(t)}){\}}_t=1,2,3,4$ are given as follows:

$,x^{(t)},y^{(t)}$

$(x^{(1)},y^{(1)}),[1,0,1{]}^T,2$

$(x^{(2)},y^{(2)}),[1,1,1{]}^T,2\mathrm{.}7$

$(x^{(3)},y^{(3)}),[1,1,-1{]}^T,-0\mathrm{.}7$

$(x^{(4)},y^{(4)}),[-1,1,1{]}^T,2$

Also, we have $=[0,1,2{]}^T.$

Compute the value of

$R_n()=\frac{1}{4}{\displaystyle \underset{?}{\overset{?}{}}}4Los{s}_h(y^{(t)}-*x^{(t)})$