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ISYE 6501 Final exam 2026-
2027 Isye 6501Test Bank
Questions and Correct
Answers Rated A+
What is unstructured data? - ANSWERS-Data that
is not easily described and stored
(e.g., written text)
A survey of 25 people recorded each person's family
size and type of car. Which of these is a data point?
A. The 14th person's family size and car type B.
The 14th person's family size
C.The car type of each person - ANSWERS-A. A
data point is all the information about one
observation
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The farther the wrongly classified point is from the
line ___ - ANSWERS-The bigger the mistake we've
made
The term including the margin gets larger so the
importance of a large margin out weights avoiding
mistakes and classifying known data samples. -
ANSWERS-As lambda gets larger
That term also drops towards zero, so the
importance of minimizing mistakes and classifying
known data points outweighs having a large margin.
- ANSWERS-As lambda drops towards zero
What can SVMs be used for - ANSWERS-to find a
classifier with maximum seperation or margin
between the two sets of points?
When to use SVM? - ANSWERS-If it's impossible
to avoid classification errors, SVM can find a
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classifier that trades off reducing errors and
enlarging the margin.
Error for data point j - ANSWERS-What does this
formula describe?
Total error - ANSWERS-What does this formula
describe ?
To maximize the distance between the two lines
what do we need to minimize? -
ANSWERS-
m_j > 1 - ANSWERS-What value do we give for
more costly errors
Giving a bad loan is twice as costly as withholding a
good loan? - ANSWERS-What does this mean in
the context of giving a loan?
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m_j < 1 - ANSWERS-What value do we give for
less costly errors?
Why is it important to scale our data when using
SVM? - ANSWERS-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.
what does it signify when a coefficient for a
classifier is close to zero - ANSWERS-it means
the corresponding attribute is probably not relevant
What do kernel methods allow for in SVMs -
ANSWERS-nonlinear classifiers
What is the common range for scaled data? -
ANSWERS-between 0 and 1
What is the formula for min-max scaling? -
ISYE 6501 Final exam 2026-
2027 Isye 6501Test Bank
Questions and Correct
Answers Rated A+
What is unstructured data? - ANSWERS-Data that
is not easily described and stored
(e.g., written text)
A survey of 25 people recorded each person's family
size and type of car. Which of these is a data point?
A. The 14th person's family size and car type B.
The 14th person's family size
C.The car type of each person - ANSWERS-A. A
data point is all the information about one
observation
,2 | Page
The farther the wrongly classified point is from the
line ___ - ANSWERS-The bigger the mistake we've
made
The term including the margin gets larger so the
importance of a large margin out weights avoiding
mistakes and classifying known data samples. -
ANSWERS-As lambda gets larger
That term also drops towards zero, so the
importance of minimizing mistakes and classifying
known data points outweighs having a large margin.
- ANSWERS-As lambda drops towards zero
What can SVMs be used for - ANSWERS-to find a
classifier with maximum seperation or margin
between the two sets of points?
When to use SVM? - ANSWERS-If it's impossible
to avoid classification errors, SVM can find a
,3 | Page
classifier that trades off reducing errors and
enlarging the margin.
Error for data point j - ANSWERS-What does this
formula describe?
Total error - ANSWERS-What does this formula
describe ?
To maximize the distance between the two lines
what do we need to minimize? -
ANSWERS-
m_j > 1 - ANSWERS-What value do we give for
more costly errors
Giving a bad loan is twice as costly as withholding a
good loan? - ANSWERS-What does this mean in
the context of giving a loan?
, 4 | Page
m_j < 1 - ANSWERS-What value do we give for
less costly errors?
Why is it important to scale our data when using
SVM? - ANSWERS-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.
what does it signify when a coefficient for a
classifier is close to zero - ANSWERS-it means
the corresponding attribute is probably not relevant
What do kernel methods allow for in SVMs -
ANSWERS-nonlinear classifiers
What is the common range for scaled data? -
ANSWERS-between 0 and 1
What is the formula for min-max scaling? -
