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Examen

ISYE_6501 Questions With Answers.

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Subido en
21-05-2023
Escrito en
2020/2021

ISYE_6501 Questions With Answers. Question 0 -- Practice with Drag & Drop 0 points possible (ungraded)  Keyboard Help Some of the quiz questions are Drag-and-Drop. You'll need to drag one or more answers to a location. Some answers might not be used at all, and some answers will be used once. To get full credit you might need to drag more than one answer to some locations, just one answer to other locations, and some locations might not have any correct answers. Please do this quick practice question. The question will give you feedback to make sure you've done it correctly, but the real quiz questions will not. x=1,y=7 x=2,y=3 x=1,y=4 3/3/2020 GT Students and Verified | Midterm Quiz 1 | ISYE6501x Courseware | edX FEEDBACK  Correctly placed 3 items.  Good work! You have completed this drag and drop problem. Note that: (1) There are two places you could've put (x=2,y=3); either one would be correct. (2) One location (x+y=2) had nothing dragged to it. Another location had two answers dragged to it. (3) One choice (x=1,y=7) was not dragged anywhere, since it wasn't correct for anything. You have used 1 of 10 attempts.  Reset Submit  Show Answer Question 1 9/13 points (graded)  Keyboard Help Drag each of the 13 models/methods to one of the 5 categories of question it is commonly used for, unless no correct category is listed for it. For models/methods that have more than one correct category, choose any one correct category; for models/methods that have no correct category listed, do not drag them. x=1,y=6 Principal component analysis 3/3/2020 GT Students and Verified | Midterm Quiz 1 | ISYE6501x Courseware | edX FEEDBACK  Correctly placed 8 items.  Misplaced 4 items. Good work! You have completed this drag and drop problem. You have used 1 of 1 attempts.  Show Answer Submit  Reset CART k-nearest-neighbor Random forest k-means Linear regression Logistic regression Support vector machine ARIMA Cross validation CUSUM Exponential smoothing GARCH 3/3/2020 GT Students and Verified | Midterm Quiz 1 | ISYE6501x Courseware | edX Question 2 3.0/3.0 points (graded) Select all of the following models that are designed for use with attribute/feature data (i.e., not time-series data):  You have used 1 of 1 attempt  Final attempt was used, highest score is 9.0 k-nearest-neighbor Support vector machine Random forest GARCH Logistic regression Principal component analysis Exponential smoothing Linear regression CUSUM

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3/3/2020 GT Students and Verified | Midterm Quiz 1 | ISYE6501x Courseware | edX




Good Luck!



Question 0 -- Practice with Drag & Drop
0 points possible (ungraded)
 Keyboard Help
Some of the quiz questions are Drag-and-Drop. You'll need to drag one or more answers
to a location.

Some answers might not be used at all, and some answers will be used once. To get full
credit you might need to drag more than one answer to some locations, just one answer
to other locations, and some locations might not have any correct answers.

Please do this quick practice question. The question will give you feedback to make sure
you've done it correctly, but the real quiz questions will not.



x=1,y=7



x=2,y=3 x=1,y=4






,3/3/2020 GT Students and Verified | Midterm Quiz 1 | ISYE6501x Courseware | edX




x=1,y=6




Submit You have used 1 of 10 attempts.



 
Reset Show Answer



FEEDBACK
 Correctly placed 3 items.

 Good work! You have completed this drag and drop problem. Note that: (1) There are two places
you could've put (x=2,y=3); either one would be correct. (2) One location (x+y=2) had nothing
dragged to it. Another location had two answers dragged to it. (3) One choice (x=1,y=7) was not
dragged anywhere, since it wasn't correct for anything.




Question 1
9/13 points (graded)

 Keyboard Help
Drag each of the 13 models/methods to one of the 5 categories of question it is commonly
used for, unless no correct category is listed for it. For models/methods that have more
than one correct category, choose any one correct category; for models/methods that
have no correct category listed, do not drag them.



Principal component
analysis




https://courses.edx.org/courses/course-v1:GTx+ISYE6501x+1T2020/courseware/a8e7783f3b6d4b21bbf5720bb6f02a92/5b27328248f3436fac8492b2… 3/26

, 3/3/2020 GT Students and Verified | Midterm Quiz 1 | ISYE6501x Courseware | edX




CART k-nearest-neighbor Random forest




k-means




Linear regression Logistic regression


Support vector machine


ARIMA Cross validation CUSUM


Exponential smoothing



GARCH




Submit You have used 1 of 1 attempts.



 
Reset Show Answer



FEEDBACK
 Correctly placed 8 items.

 Misplaced 4 items.

Good work! You have completed this drag and drop problem.




https://courses.edx.org/courses/course-v1:GTx+ISYE6501x+1T2020/courseware/a8e7783f3b6d4b21bbf5720bb6f02a92/5b27328248f3436fac8492b2… 4/26

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Subido en
21 de mayo de 2023
Número de páginas
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Escrito en
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