From 87d3a1b320dee04d11e7ac67cb599b30644cb48e Mon Sep 17 00:00:00 2001
From: Yousuke Takada <yousuketakada@gmail.com>
Date: Sat, 7 Apr 2018 15:48:18 +0900
Subject: [PATCH] Edit: A Bayesian model that exhibits overfitting (#10)

---
 prml_errata.tex | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/prml_errata.tex b/prml_errata.tex
index 66db56c..644b825 100644
--- a/prml_errata.tex
+++ b/prml_errata.tex
@@ -1970,7 +1970,8 @@ \subsubsection*{#1}
 suppose that the precision~$\beta$ of the target~$t$ in the likelihood~(3.8) is very large
 whereas the precision~$\alpha$ of the parameters~$\mathbf{w}$ in the prior~(3.52) is very small
 (i.e., the conditional distribution of $t$ given $\mathbf{w}$ is narrow whereas
-the prior over $\mathbf{w}$ is broad so that the regularization is insufficient).
+the prior over $\mathbf{w}$ is broad), leading to insufficient \emph{regularization}
+(see also Section~3.1.4).
 Then, the posterior~$p(\mathbf{w}|\bm{\mathsf{t}})$ given the data set~$\bm{\mathsf{t}}$ is
 sharply peaked around the maximum likelihood estimate~$\mathbf{w}_{\text{ML}}$ and
 the predictive~$p(t|\bm{\mathsf{t}})$ is also sharply peaked