docs(blog): update precision_expr assignment

Co-authored-by: Deepyaman Datta <[email protected]>

docs/posts/classification-metrics-on-the-backend/index.qmd

@@ -187,7 +187,7 @@ fn = t.actual.sum() - tp
 tn = t.actual.count() - tp - fp - fn
 
 accuracy_expr = (tp + tn) / (tp + tn + fp + fn)
-precision_expr = tp / (tp + fp)
+precision_expr = tp / t.prediction.sum()
 recall_expr = tp / (tp + fn)
 f1_score_expr = 2 * (precision_expr * recall_expr) / (precision_expr + recall_expr)