Wie mache ich das?
\begin{algorithm}
\caption{GPR Prediction} \label{alg:gprprediction}
\algorithmicrequire{ Standardized set of training input-data \inm{\mathbf{X}}, set of training output-data \inm{\mathbf{y}}, set of test input-data \inm{\mathbf{X}_*}, covariance function \inm{\mathrm{k}}, learned parameters \inm{\boldsymbol\uptheta_I}}\\
\algorithmicensure{ Model prediction \inm{\mathbf{m}_{f_{\mathbf{X}_*}}, \boldsymbol\Sigma_{f_{\mathbf{X}_*}}}}
\begin{algorithmic}
\Function{\inm{\mathbf{m}_{f_{\mathbf{X}_*}}, \boldsymbol\Sigma_{f_{\mathbf{X}_*}}=}Prediction}{\inm{\mathbf{X},\mathbf{y},\mathbf{X}_*,\mathrm{k}\boldsymbol\uptheta_I}}:
\State \inm{L = \text{cholesky}(K)}; (pre-computation)
\State \inm{\boldsymbol\upalpha = L^T\backslash(L\backslash\mathbf{y})}; (pre-computation)
\State \inm{\mathbf{v} = LK_{NN_*}};
\State \inm{\mathbf{m}_{f_{\mathbf{X}_*}}=K_{N_*N}\boldsymbol\upalpha};
\State \inm{\boldsymbol\Sigma_{f_{\mathbf{X}_*}}= \text{diag}(K_{N_*N_*})- \mathbf{v}^T\mathbf{v}};
\EndFunction
\end{algorithmic}
\end{algorithm}
Vielen dank.