ISYE 6501 - Final Exam
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1. What do descriptive questions ask? What happened? (e.g.,
which customers are most
alike)
2. What do predictive questions ask? What will happen? (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 situation ex-
pressed 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
mistakes.
7. What does it mean when the classifier/decision The horizontal attribute is
boundary is almost parallel to the vertical x-axis? all that is needed.
8. What does it mean when the classifier/decision The vertical attribute is all
boundary is almost parallel to the horizontal y-axis? that is needed.
9. What is time-series data? The same data recorded
over time often recorded
at equal intervals
, ISYE 6501 - Final Exam
Study online at https://quizlet.com/_4t1znp
10. What is quantitative data? Number with a mean-
ing: higher means more,
lower means less (e.g.,
age, sales, temperature,
income)
11. What is categorical data? Numbers w/o meaning
(e.g., zip codes), non-nu-
meric (e.g., hair color), bi-
nary 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 structured way
15. What is unstructured data? Data that is not easily de-
scribed 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 all the infor-
A. The 14th person's family size and car type mation about one obser-
vation
, ISYE 6501 - Final Exam
Study online at https://quizlet.com/_4t1znp
B. The 14th person's family size
C.The car type of each person
17. The farther the wrongly classified point is from the line The bigger the mistake
___ we've made
18. The term including the margin gets larger so the im- As lambda gets larger
portance of a large margin out weights avoiding mis-
takes and classifying known data samples.
19. That term also drops towards zero, so the importance As lambda drops towards
of minimizing mistakes and classifying known data zero
points outweighs having a large margin.
20. What can SVMs be used for to find a classifier with
maximum seperation or
margin between the two
sets of points?
21. When to use SVM? If it's impossible to avoid
classification errors, SVM
can find a classifier that
trades off reducing errors
and enlarging the margin.
22. Error for data point j What does this formula
describe?
23. Total error What does this formula
describe ?
, ISYE 6501 - Final Exam
Study online at https://quizlet.com/_4t1znp
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 costly errors
26. Giving a bad loan is twice as costly as withholding a What does this mean in
good loan? the context 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 SVM? We're looking to minimize
the sum of the squares
of the coefficients, but if
our data has very different
scales a small change in
one could swamp a huge
change in the other.
29. what does it signify when a coefficient for a classifier it means the correspond-
is close to zero ing attribute is probably
not relevant
30. What do kernel methods allow for in SVMs nonlinear classifiers
31. What is the common range for scaled data? between 0 and 1
Study online at https://quizlet.com/_4t1znp
1. What do descriptive questions ask? What happened? (e.g.,
which customers are most
alike)
2. What do predictive questions ask? What will happen? (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 situation ex-
pressed 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
mistakes.
7. What does it mean when the classifier/decision The horizontal attribute is
boundary is almost parallel to the vertical x-axis? all that is needed.
8. What does it mean when the classifier/decision The vertical attribute is all
boundary is almost parallel to the horizontal y-axis? that is needed.
9. What is time-series data? The same data recorded
over time often recorded
at equal intervals
, ISYE 6501 - Final Exam
Study online at https://quizlet.com/_4t1znp
10. What is quantitative data? Number with a mean-
ing: higher means more,
lower means less (e.g.,
age, sales, temperature,
income)
11. What is categorical data? Numbers w/o meaning
(e.g., zip codes), non-nu-
meric (e.g., hair color), bi-
nary 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 structured way
15. What is unstructured data? Data that is not easily de-
scribed 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 all the infor-
A. The 14th person's family size and car type mation about one obser-
vation
, ISYE 6501 - Final Exam
Study online at https://quizlet.com/_4t1znp
B. The 14th person's family size
C.The car type of each person
17. The farther the wrongly classified point is from the line The bigger the mistake
___ we've made
18. The term including the margin gets larger so the im- As lambda gets larger
portance of a large margin out weights avoiding mis-
takes and classifying known data samples.
19. That term also drops towards zero, so the importance As lambda drops towards
of minimizing mistakes and classifying known data zero
points outweighs having a large margin.
20. What can SVMs be used for to find a classifier with
maximum seperation or
margin between the two
sets of points?
21. When to use SVM? If it's impossible to avoid
classification errors, SVM
can find a classifier that
trades off reducing errors
and enlarging the margin.
22. Error for data point j What does this formula
describe?
23. Total error What does this formula
describe ?
, ISYE 6501 - Final Exam
Study online at https://quizlet.com/_4t1znp
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 costly errors
26. Giving a bad loan is twice as costly as withholding a What does this mean in
good loan? the context 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 SVM? We're looking to minimize
the sum of the squares
of the coefficients, but if
our data has very different
scales a small change in
one could swamp a huge
change in the other.
29. what does it signify when a coefficient for a classifier it means the correspond-
is close to zero ing attribute is probably
not relevant
30. What do kernel methods allow for in SVMs nonlinear classifiers
31. What is the common range for scaled data? between 0 and 1
