ISYE 6501 Midterm 1
• Due Mar 15 at 2am
• Points 100
• Questions 45
• Available until Mar 15 at 2am
• Time Limit 95 Minutes
Instructions
This quiz was locked Mar 15 at 2am.
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ISYE 6501 Midterm 1
• Due Mar 15 at 2am
• Points 100
• Questions 45
• Available until Mar 15 at 2am
• Time Limit 95 Minutes
Instructions
This quiz was locked Mar 15 at 2am.
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question.
Question 1
9 / 13 pts
1. For each of the 13 models/methods, select the choice that includes the category of question
it is commonly used for. For models/methods that have more than one correct category, the
one it is most commonly used for; for models/methods that have no correct category listed,
select "None".
i. ARIMA Response prediction
ii. CART Classification and Response prediction
iii. Cross validation Validation
iv. CUSUM None of the other choices
v. Exponential smoothing Response prediction
vi. GARCH Variance estimation
vii. kmeans Classification
viii. k-nearest-neighbor Clustering
ix. Linear regression Validation
x. Logistic regression Classification and Response prediction
xi. Principal component analysis Validation
xii. Random forest Classification and Response prediction
xiii. Support vector machine ClassificationAnswer 1:
Classification
Clustering
Correct!
Response prediction
Validation
Variance estimation
None of the other choices
Answer 2:
Correct!
Classification and Response prediction
Clustering
Validation
Variance estimation
None of the other choices
Answer 3:
Classification and Response predictionClustering
Correct!
Validation
Variance estimation
None of the other choices
Answer 4:
Classification and Response prediction
Clustering
Validation
Variance estimation
Correct!
None of the other choices
Answer 5:
Classification
Clustering
Correct!
Response prediction
ValidationVariance estimation
None of the other choices
Answer 6:
Classification
Clustering
Respnse prediction
Validation
Correct!
Variance estimation
None of the other choices
Answer 7:
You Answered
Classification
Correct Answer
Clustering
Response prediction
Validation
Variance estimationNone of the other choices
Answer 8:
Correct Answer
Classification and Response prediction
You Answered
Clustering
Validation
Variance estimation
None of the other choices
Answer 9:
Classification
Clustering
Correct!
Response prediction
Validation
Variance estimation
None of the other choices
Answer 10:
Correct!
Classification and Response predictionClustering
Validation
Variance estimation
None of the other choices
Answer 11:
Classification and Response prediction
Clustering
Validation
Variance estimation
Correct!
None of the other choices
Answer 12:
Correct!
Classification and Response prediction
Clustering
Validation
Variance estimationNone of the other choices
Answer 13:
Correct!
Classification
Clustering
Response prediction
Validation
Variance estimation
None of the other choices
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Question 2
3 / 3 pts
2. For each of the following models, specify whether it is designed for use with
attribute/feature data or time-series data:
a. Exponential smoothing [ Select ] ["Attribute/feature data", "Time series data"]
b. ARIMA [ Select ] ["Attribute/feature data", "Time series data"]
c. k-means [ Select ] ["Attribute/feature data", "Time series data"]
d. Principal component analysis [ Select ] ["Attribute/feature data", "Time series
data"]
e. Linear regression [ Select ] ["Attribute/feature data", "Time series data"]
f. k-nearest-neighbor Attribute/feature data
g. Random forest [ Select ] ["Attribute/feature data", "Time series data"]
h. CUSUM [ Select ] ["Attribute/feature data", "Time series data"]
i. Logistic regression [ Select ] ["Attribute/feature data", "Time series data"]
j. Support vector machine [ Select ] ["Attribute/feature data", "Time series data"]
k. GARCH [ Select ] ["Attribute/feature data", "Time series data"]
Answer 1:Attribute/feature data
Correct!
Time series data
Answer 2:
Attribute/feature data
Correct!
Time series data
Answer 3:
Correct!
Attribute/feature data
Time series data
Answer 4:
Correct!
Attribute/feature data
Time series data
Answer 5:
Correct!
Attribute/feature data
Time series data
Answer 6:
Correct!
Attribute/feature data
Time series dataAnswer 7:
Correct!
Attribute/feature data
Time series data
Answer 8:
Attribute/feature data
Correct!
Time series data
Answer 9:
Correct!
Attribute/feature data
Time series data
Answer 10:
Correct!
Attribute/feature data
Time series data
Answer 11:
Attribute/feature data
Correct!
Time series data
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INFORMATION FOR QUESTIONS 3-12Figures A and B show the training data for a soft classification problem, using two predictors
(x1 and x2) to separate between black and white points. The dashed lines are the classifiers
found using SVM. Figure A uses a linear kernel, and Figure B uses a nonlinear kernel that
required fitting 16 parameter values.
Figure AFigure B
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INSTRUCTIONS FOR QUESTIONS 3-11
For each statement in Questions 3-11, select the choice that makes the statement true.
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Question 3
0.6 / 0.6 pts
Figure A's classifier IS NOT based on the values of both x1 and x2.
Answer 1:
IS
Correct!
IS NOTMove To... This element is a more accessible alternative to drag & drop reordering. Press Enter or Space
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Question 4
0.6 / 0.6 pts
Figure A's classifier WOULD probably perform worse on test data than on the training data.
Answer 1:
Correct!
WOULD
WOULD NOT
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Question 5
0.6 / 0.6 pts
Figure A's classifier has a WIDER margin than Figure B's classifier in the training data.
Answer 1:
NARROWER
Correct!
WIDER
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Question 6
0 / 0.6 pts
Figure A's classifier incorrectly classifies EXACTLY 4 black points as white in the training
data.
Answer 1:
EXACTLY 4
Correct!
MORE OR FEWER THAN 4Move To... This element is a more accessible alternative to drag & drop reordering. Press Enter or Space
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Question 7
0.6 / 0.6 pts
Figure A DOES NOT SHOW that the black point (7.2,1.4) is an outlier.
Answer 1:
Correct!
DOES NOT SHOW
SHOWS
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Question 8
0.75 / 0.75 pts
Figure B's classifier has a NARROWER margin in the training data than Figure A's classifier.
Answer 1:
Correct!
NARROWER
WIDER
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Question 9
0 / 0.75 pts
Figure B's classifier would probably perform BETTER on test data than on training data.
AnISYE 6501 Midterm 1
• Due Mar 15 at 2am
• Points 100
• Questions 45swer 1:
ISYE 6501 Midterm 1
• Due Mar 15 at 2am
• Points 100
• Questions 45
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