From 843b61277de2b9938ba677238add5a3b3564e10f Mon Sep 17 00:00:00 2001 From: jannes Date: Mon, 7 Oct 2024 13:27:17 +0200 Subject: [PATCH] fix citation --- 15-eco.Rmd | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/15-eco.Rmd b/15-eco.Rmd index 95a4da453..f537957cf 100644 --- a/15-eco.Rmd +++ b/15-eco.Rmd @@ -406,7 +406,7 @@ The observations falling into the left branch have a mean NMDS\index{NMDS} score Overall, we can interpret the tree as follows: the higher the elevation, the higher the NMDS\index{NMDS} score becomes. This means that the simple decision tree has already revealed four distinct floristic assemblages. For a more in-depth interpretation, please refer to Section \@ref(predictive-mapping). -Decision trees have a tendency to overfit\index{overfitting}, that is, they mirror too closely the input data including its noise which in turn leads to bad predictive performances [Section \@ref(intro-cv); @james_introduction_2013]. +Decision trees have a tendency to overfit\index{overfitting}, that is, they mirror too closely the input data including its noise which in turn leads to bad predictive performances [Section \@ref(intro-cv), @james_introduction_2013]. Bootstrap aggregation (bagging) is an ensemble technique that can help to overcome this problem. Ensemble techniques simply combine the predictions of multiple models. Thus, bagging takes repeated samples from the same input data and averages the predictions.