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Course Midter… Midter… Midter…
Midterm Quiz 1 - Audit Learners
90 Minute Time Limit
Instructions
Work alone. Do not collaborate with or copy from anyone else.
You may use any of the following resources:
One sheet (both sides) of handwritten (not photocopied or scanned) notes
If any question seems ambiguous, use the most reasonable interpretation (i.e. don't be like Calvin):
Good Luck!
Question 1
12/13 points (graded)
Keyboard Help
Drag each model to a type of question it is commonly used for. For models that have more than one
correct answer, choose any one correct answer; for models that have no correct answer listed, do not
drag them.
CUSUM
https://courses.edx.org/courses/course-v1:GTx+ISYE6501x+3T2018/courseware/a8e7783f3b6d4b21bbf5720bb6f02a92/7244922e3d3a401994e816b… 1/16
,03/10/2019 Midterm Quiz 1 - Audit Learners | Midterm Quiz 1 - Audit Learners | ISYE6501x Courseware | edX
CART k-nearest-neighbor Support vector machine
k-means
ARIMA Exponential smoothing Linear regression
Logistic regression Principal component analysis Random forest
Cross validation
GARCH
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FEEDBACK
Correctly placed 11 items.
Misplaced 1 item.
Good work! You have completed this drag and drop problem.
Final attempt was used, highest score is 12.0
Question 2
3.0/3.0 points (graded)
Select all of the following models that are designed for use with time series data:
ARIMA
CUSUM
Exponential Smoothing
https://courses.edx.org/courses/course-v1:GTx+ISYE6501x+3T2018/courseware/a8e7783f3b6d4b21bbf5720bb6f02a92/7244922e3d3a401994e816b… 2/16
, 03/10/2019 Midterm Quiz 1 - Audit Learners | Midterm Quiz 1 - Audit Learners | ISYE6501x Courseware | edX
GARCH
k-nearest-neighbor
Submit You have used 1 of 1 attempt
INFORMATION FOR QUESTIONS 3A, 3C
FIGURES A AND B SHOW THE TRAINING DATA FOR A CLASSIFICATION PROBLEM, USING TWO
PREDICTORS (X1 AND X2 ) TO SEPARATE BETWEEN BLACK AND WHITE POINTS. THE DASHED LINES
ARE THE CLASSIFIERS.
Figure A Figure B
Question 3a
3.0/3.0 points (graded)
Figure B shows an SVM classi cation using a complex nonlinear kernel. (To get this perfect t to the training data, it required
tting 16 parameter values!) Which of the following is true?
Figure B is a very good classi er, because it correctly classi es all of the training data.
Figure B is a very good classi er, because the model’s complexity shows that it is a deep analysis.
Figure B is a bad classi er to use, because it is over t.
Figure B might or might not be a good classi er, because it is over t.
Submit You have used 1 of 1 attempt
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