1. What do descriptive questions ask? What happened?
(e.g., which cus-
tomers are most
alike)
2. What do predictive questions ask? What will hap-
pen? (e.g., what
will Google's stock
price be?)
3. What do prescriptive questions ask? What action(s)
would be best?
(e.g., where to put
traffic lights)
4. What is a model? Real-life situa-
tion expressed as
math.
5. What do classifiers help you do? differentiate
6. What is a soft classifier and when is it used? In some cases,
there won't be a
line that separates
all of the labeled
examples. So we
use a classifier
that minimizes the
number of mis-
takes.
7. What does it mean when the classifier/decision The horizontal at-
boundary is almost parallel to the vertical x-axis? tribute is all that is
needed.
8. What does it mean when the classifier/decision The vertical at-
boundary is almost parallel to the horizontal y-axis? tribute is all that is
needed.
9. What is time-series data?
, ISYE 6501 - Final Exam
The same data
recorded over
time often record-
ed at equal inter-
vals
10. What is quantitative data? Number with a
meaning: higher
means more, low-
er means less
(e.g., age, sales,
temperature, in-
come)
11. What is categorical data? Numbers w/o
meaning (e.g., zip
codes), non-nu-
meric (e.g., hair
color), binary data
(e.g., male/fe-
male, yes/no,
on/off)
12. Which of these is time series data? A
A. The average cost of a house in the United States
every year since 1820
B. The height of each professional basketball player
in the NBA at the start of the season
13. Which of these is structured data? B
A. The contents of a person's Twitter feed
B. The amount of money in a person's bank account
14. What is structured data? Data that can be
stores in a struc-
tured way
15. What is unstructured data? Data that is not
easily described
, ISYE 6501 - Final Exam
and stored (e.g.,
written text)
16. A survey of 25 people recorded each person's family A.
size and type of car. Which of these is a data point? A data point is
A. The 14th person's family size and car type all the information
B. The 14th person's family size about one obser-
C.The car type of each person vation
17. The farther the wrongly classified point is from the The bigger the
line ___ mistake we've
made
18. The term including the margin gets larger so the As lambda gets
importance of a large margin out weights avoiding larger
mistakes and classifying known data samples.
19. That term also drops towards zero, so the importance As lambda drops
of minimizing mistakes and classifying known data towards zero
points outweighs having a large margin.
20. What can SVMs be used for to find a classifi-
er with maximum
seperation or mar-
gin between the
two sets of points?
21. When to use SVM? If it's impossible
to avoid classifica-
tion errors, SVM
can find a clas-
sifier that trades
off reducing errors
and enlarging the
margin.
22. Error for data point j What does this for-
mula describe?
, ISYE 6501 - Final Exam
23. Total error What does this for-
mula describe ?
24. To maximize the distance between the two lines what
do we need to minimize?
25. m_j > 1 What value do we
give for more cost-
ly errors
26. Giving a bad loan is twice as costly as withholding a What does this
good loan? mean in the con-
text of giving a
loan?
27. m_j < 1 What value do we
give for less costly
errors?
28. Why is it important to scale our data when using We're looking to
SVM? minimize the sum
of the squares
of the coefficients,
but if our data
has very differ-
ent scales a small
change in one
could swamp a
huge change in
the other.
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