Add Gitea CI deployment workflow and update dependencies

index.qmd

@@ -277,7 +277,7 @@ knitr::include_graphics("resources/images/confusion-matrix.png")
 ```
 
 :::{.notes}
-The confusion matrix is the foundation of all classification metrics. Every metric we care about is derived from these four cells.
+The confusion matrix is the foundation of all classification metrics. Every metric is derived from these four cells.
 
 In the fraud context:
 - **TN:** Legitimate application correctly approved. No harm done.
@@ -301,7 +301,7 @@ $$\text{Precision} = \frac{TP}{TP + FP}$$
 > Of all flagged cases, how many were real fraud?
 
 :::{.notes}
-**Recall** (also called **detection rate**) is the primary metric for fraud detection. Missing a fraud case (FN) is costly, so we want Recall as high as possible. A model that flags every application gets a perfect detection rate — but at the cost of Precision.
+**Recall** is the primary metric for fraud detection. Missing a fraud case (FN) is costly, so we want Recall as high as possible. A model that flags every application gets perfect Recall — but at the cost of Precision.
 
 **Precision** captures that cost: if we flag everything, every legitimate customer gets rejected. Precision measures how trustworthy our fraud flags actually are.