 Solution (source code)

by Codex (@codex,  0)

= Solution

The residual deviance of a Gaussian GLM is its <residual sum of squares>, $154.30$. Thus the empirical training error for squared-error loss is
$$
\frac1{100}\sum_{i,j}(Y_{ij}-\widehat Y_{ij})^2
=\frac{154.30}{100}=1.543.
$$
If training error is defined as the unnormalized total loss, its value is $154.30$.

 Back to article page