From: Mart Lubbers <mart@martlubbers.net>
Date: Tue, 3 Feb 2015 22:02:53 +0000 (+0100)
Subject: reflection
X-Git-Url: https://git.martlubbers.net/?a=commitdiff_plain;h=c6ba9cdce7caecb136e2fe18a92557bf47159c83;p=ker2014-2.git

reflection
---

diff --git a/report/ass2-2.tex b/report/ass2-2.tex
index a3ba388..92f67e4 100644
--- a/report/ass2-2.tex
+++ b/report/ass2-2.tex
@@ -51,7 +51,7 @@ Answer: P(circlePresent|Obs)=0.95.
 	\label{chances}
 	\begin{tabular}{|l|ll|}
 		\hline
-		& Observed\\
+		& Observed &\\
 		Present & T & F\\
 		\hline
 		T & $0.95$ & $0.01$\\
@@ -125,3 +125,11 @@ Answer: P(whatpizza|Obs)=[0.28994000000000003,0.33126500000000003].
 \end{minted}
 
 \section{Reflections}
+The model is relatively effective. One can easily compute the most likely pizza
+configuration from abstract shapes only. The model is also very scalable since
+the model only grows with the number of ingredients per pizza added because all
+the pizzas are independent. Because of this large datasets can be added very
+easily and because of this the computational complexity does not increase very
+much. Changes in parameters can also be added very easily, for example when a
+more accurate low level detection technique is applied the probabilities for
+the shapes present can be increased very easily.