Bias
Bias is the error between average model prediction (i.e. \(E[g(x)]\)) and the ground truth \(f(x)\).
Bias indicates the training error.
\[
Bias^2 = E[(E[g(x)]-f(x))^2]
\]
Bias is the error between average model prediction (i.e. \(E[g(x)]\)) and the ground truth \(f(x)\).
Bias indicates the training error.