add the

15-eco.Rmd

@@ -427,7 +427,7 @@ The code in this section largely follows the steps we have introduced in Section
 The only differences are the following:
 
 1. The response variable is numeric, hence a regression\index{regression} task will replace the classification\index{classification} task of Section \@ref(svm)
-1. Instead of the AUROC\index{AUROC} which can only be used for categorical response variables, we will use the root mean squared error (RMSE\index{RMSE}) as performance measure
+1. Instead of the AUROC\index{AUROC} which can only be used for categorical response variables, we will use the root mean squared error (RMSE\index{RMSE}) as the performance measure
 1. We use a random forest\index{random forest} model instead of a support vector machine\index{SVM} which naturally goes along with different hyperparameters\index{hyperparameter}
 1. We are leaving the assessment of a bias-reduced performance measure as an exercise to the reader (see Exercises).
 Instead we show how to tune hyperparameters\index{hyperparameter} for (spatial) predictions