Computer Science > EXAM > Georgia Institute Of Technology ISYE 6501 Midterm Quiz 1 with Correct Answers (All)

Georgia Institute Of Technology ISYE 6501 Midterm Quiz 1 with Correct Answers

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Georgia Institute Of Technology ISYE 6501 Midterm Quiz 1 with Correct Answers Step 2: Midterm Quiz 1 - GT Students (Launch Proctortrack Õrst before taking the Midterm Quiz 1) 95 Minute Time Limit In... structions Work alone. Do not coll aborate with or copy from anyone else. Y ou 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 0 -- Practice with Drag & Drop 0 points possible (ungraded)  Keyboard Help11/11/2019 Step 2: Midterm Quiz 1 - GT Students (Launch Proctortrack first before taking the Midterm Quiz 1) | Step 2: Midterm Quiz 1 - GT St… https://courses.edx.org/courses/course-v1:GTx+ISYE6501x+2T2019b/courseware/a8e7783f3b6d4b21bbf5720bb6f02a92/7d4f7b9ba5e84153afb… 2/24 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. 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 6 of 10 attempts.  Reset Submit  Show Answer Question 1 9/13 points (graded)  Keyboard Help x=1, y=7 x=2, y=3 x=1, y=4 x=1, y=611/11/2019 Step 2: Midterm Quiz 1 - GT Students (Launch Proctortrack first before taking the Midterm Quiz 1) | Step 2: Midterm Quiz 1 - GT St… https://courses.edx.org/courses/course-v1:GTx+ISYE6501x+2T2019b/courseware/a8e7783f3b6d4b21bbf5720bb6f02a92/7d4f7b9ba5e84153afb… 3/24 Drag each model or method to a category of question it is commonly used for. 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. FEEDBACK  Correctly placed 8 items.  Misplaced 1 item. Submit You have used 1 of 1 attempts.  Reset  Show Answer CUSUM Principal component analysis Support vector machine k-means ARIMA CART Exponential smoothing k-nearest-neighbor Linear regression Logistic regression Random forest Cross validation GARCH11/11/2019 Step 2: Midterm Quiz 1 - GT Students (Launch Proctortrack first before taking the Midterm Quiz 1) | Step 2: Midterm Quiz 1 - GT St… https://courses.edx.org/courses/course-v1:GTx+ISYE6501x+2T2019b/courseware/a8e7783f3b6d4b21bbf5720bb6f02a92/7d4f7b9ba5e84153afb… 4/24 Question 2 2.19/3.0 points (graded) Select all of the following models that are designed for use with time series data:  You have used 1 of 1 attempt  Did not place 3 required items.  Good work! You have completed this drag and drop problem.  Final attempt was used, highest score is 9.0 k-nearest-neighbor Principal component analysis ARIMA  k-means CUSUM  Logistic regression GARCH  Exponential smoothing  Random forest Linear regression Support vector machine Submit11/11/2019 Step 2: Midterm Quiz 1 - GT Students (Launch Proctortrack first before taking the Midterm Quiz 1) | Step 2: Midterm Quiz 1 - GT St… https://courses.edx.org/courses/course-v1:GTx+ISYE6501x+2T2019b/courseware/a8e7783f3b6d4b21bbf5720bb6f02a92/7d4f7b9ba5e84153afb… 5/24 Answers are displayed within the problem Information for Questions 3a, 3b, 3c Figures A and B show the training data for a soft classiÕcation problem, using two predictors (x and x ) to separate between black and white points. The dashed lines are the classiÕers found using SVM. Figure A uses a linear kernel, and Figure B uses a nonlinear kernel that required Õtting 16 parameter values. Figure A Figure B Question 3a 2.4/3.0 points (graded) 3a. Select all of the following statements that are true.  1 2 Figure A's classiÕer is based only on the value of x2 . Figure A has fewer classiÕcation errors in the training data. Figure A's classiÕer has a wider margin in the training data. 11/11/2019 Step 2: Midterm Quiz 1 - GT Students (Launch Proctortrack first before taking the Midterm Quiz 1) | Step 2: Midterm Quiz 1 - GT St… https://courses.edx.org/courses/course-v1:GTx+ISYE6501x+2T2019b/courseware/a8e7783f3b6d4b21bbf5720bb6f02a92/7d4f7b9ba5e84153afb… 6/24 Answers are displayed within the problem Answers are displayed within the problem  You have used 1 of 1 attempt Question 3b 2.25/3.0 points (graded) 3b. Select all of the following statements that are true.  You have used 1 of 1 attempt Question 3c 1.5/3.0 points (graded) 3c. Select all of the following statements that are true. Figure A's classiÕer incorrectly classiÕes exactly 4 white points in the training data.  Figure A shows that the black point (7.2,1.4) is an outlier. Submit  Figure B's classiÕer has a narrower margin in the training data.  Figure B's classiÕer is more likely to be over-Õt.  Figure B's classiÕer incorrectly classiÕes exactly 5 white points in the training data. Figure B shows that the black point (7.2,1.4) should be white. Submit  A new point at (3,3) would be classiÕed as white by Figure A's classiÕer.11/11/2019 Step 2: Midterm Quiz 1 - GT Students (Launch Proctortrack first before taking the Midterm Quiz 1) | Step 2: Midterm Quiz 1 - GT St… https://courses.edx.org/courses/course-v1:GTx+ISYE6501x+2T2019b/courseware/a8e7783f3b6d4b21bbf5720bb6f02a92/7d4f7b9ba5e84153afb… 7/24 Answers are displayed within the problem Answers are displayed within the problem  You have used 1 of 1 attempt Question 3d 3.0/3.0 points (graded) In the soft classiÕcation SVM model where we select coeÞcients ... to minimize 3d. Select each of the following cases when we would want to decrease the value of .  You have used 1 of 1 attempt A new point at (3,3) would be classiÕed as white by Figure B's classiÕer.  A new point at (3,3) would be classiÕed as white by a -nearest-neighbor algorithm for . k 5 ≤ k ≤ 10 In Figure A, if the training data had 1000 more white points to the right of the classiÕer, a 1000-nearest-neighbor algorithm would classify a new point at (3,3) as white.  Submit  a0 am ∑max{0, 1 − ( + ) } + C j−1 n m∑i=1 aixij a0 yj ∑ i=1 m a2 i C We want a larger margin even if it induces more classiÕcation errors in the training set. We are willing to accept a smaller margin in order to reduce classiÕcation errors in the training set. Neither. Submit 11/11/2019 Step 2: Midterm Quiz 1 - GT Students (Launch Proctortrack first before taking the Midterm Quiz 1) | Step 2: Midterm Quiz 1 - GT St… https://courses.edx.org/courses/course-v1:GTx+ISYE6501x+2T2019b/courseware/a8e7783f3b6d4b21bbf5720bb6f02a92/7d4f7b9ba5e84153afb… 8/24 Answers are displayed within the problem Question 3e 0.99/3.0 points (graded) 3e. In the hard classiÕcation SVM model, it might be desirable to not put the classiÕer in a location that has equal margin on both sides... (select all correct answers):  You have used 1 of 1 attempt Information for Questions 4a, 4b, 4c Seven diàerent regression models have been Õtted, using diàerent sets of variables. The Õgure below shows the resulting adjusted R-squared value for various models, as measured by cross-validation [Show More]

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