forked from DragonflyStats/Coursera-ML
-
Notifications
You must be signed in to change notification settings - Fork 0
/
MLQuiz15Q1anomalydetection.aux.tex
20 lines (15 loc) · 1.23 KB
/
MLQuiz15Q1anomalydetection.aux.tex
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
\documentclass[]{article}
\begin{document}
\section*{Anomaly Detection}
For which of the following problems would anomaly detection be a suitable algorithm?
\begin{itemize}
\item[(i)]
Given an image of a face, determine whether or not it is the face of a particular famous individual.\\ \textbf{Conclusion} This problem is more suited to traditional supervised learning, as you want both famous and non-famous images in the training set.
\item[(ii)]
In a computer chip fabrication plant, identify microchips that might be defective. \\ \textbf{Conclusion} The defective chips are the anomalies you are looking for by modeling the properties of non-defective chips.
\item[(iii)]
Given a dataset of credit card transactions, identify unusual transactions to flag them as possibly fraudulent. \\ \textbf{Conclusion} By modeling "normal" credit card transactions, you can then use anomaly detection to flag the unusuals ones which might be fraudulent.
\item[(iv)]
From a large set of hospital patient records, predict which patients have a particular disease (say, the flu).\\ \textbf{Conclusion} Anomaly detection would not be appropriaate, as you want to train on both types of patient records rather than modeling one as "normal."
\end{itemize}
\end{document}