From 1a6bdb6652239d84a63b8131d07905c62ee5f1d8 Mon Sep 17 00:00:00 2001
From: ben-jaynes <1btjaynes@gmail.com>
Date: Thu, 21 May 2026 19:03:38 -0700
Subject: [PATCH] vault backup: 2026-05-21 19:03:38

---
 .../Class 5-21 (Ensemble Models).md                           | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/Running Start/CSB320 - Machine Learning Concepts/Class 5-21 (Ensemble Models).md b/Running Start/CSB320 - Machine Learning Concepts/Class 5-21 (Ensemble Models).md
index 9f2bb7e..8d87b27 100644
--- a/Running Start/CSB320 - Machine Learning Concepts/Class 5-21 (Ensemble Models).md	
+++ b/Running Start/CSB320 - Machine Learning Concepts/Class 5-21 (Ensemble Models).md	
@@ -32,4 +32,8 @@ bootstrap_samples = [
 	- bagging reduces model variance, not data variance
 		- (how much does model change if data changes slightly)
 	- bagging helps to make predictions more stable
+	- model variance should be low to increase prediction stability, data variance should be high so patterns are easier to find
+	- 10-25 decision trees are typically sufficient
+		- too many results in diminishing returns
+	- bagging gives high accuracy and better generalization but can be hard to interpret and have large computational costs
 	- 
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