From ab59f456e2aee73da6e65e79bd292a3bd6b4d4c3 Mon Sep 17 00:00:00 2001
From: "Jip J. Dekker" <jip@dekker.li>
Date: Fri, 25 May 2018 13:37:07 +1000
Subject: [PATCH] Add paragraph on random forest

---
 mini_proj/report/waldo.tex | 9 ++++++++-
 1 file changed, 8 insertions(+), 1 deletion(-)

diff --git a/mini_proj/report/waldo.tex b/mini_proj/report/waldo.tex
index 6ea06d2..b5fb94e 100644
--- a/mini_proj/report/waldo.tex
+++ b/mini_proj/report/waldo.tex
@@ -154,7 +154,14 @@
 
 		\paragraph{Random Forest}
 
-		\cite{randomforest}
+		\cite{randomforest} is a method that is based on classifications decision
+		trees. In a decision tree a new instances is classified by going down a
+		(binary) tree. Each non-leaf node contain a selection criteria to its
+		branches. Every leaf node contains the class that will be assigned to the
+		instance if the node is reached. In other training methods, decision trees
+		have the tendency to overfit, but in random forest a multitude of decision
+		tree is trained with a certain degree of randomness and the mean of these
+		trees is used which avoids this problem.
 
 		\subsection{Neural Network Architectures}
 		\todo{Did we only do the three in the end? (Alexnet?)}