Information Technology > EXAM > Georgia Institute Of Technology - ISYE 6501GT Students _ Final Quiz _ ISYE6501x 2020 Courseware _ (All)
GT Students Final Quiz due Dec 7, 2020 02:00 EST Completed 180 Minute Time Limit Instructions Work alone. Do not collaborate with or copy from anyone else. Work the problems in any order you wish... , but submit your answer to each before ending the exam. You may use any of the following resources: Two sheets (both sides) of handwritten (not photocopied or scanned) notes Blank scratch paper and pen/pencil If any question seems ambiguous, use the most reasonable interpretation (i.e. don't be like Calvin): Good Luck! This is the beginning of the Final Quiz. Please make sure that you submit all your answers before the time runs out. Once you submit an answer to a question, you cannot change it. There is no overall Submit button. After submitting all answers, please click the "End my Exam" button, above, before exiting from ProctorTrack to complete your exam. 12/10/2020 GT Students | Final Quiz | ISYE6501xCourseware | edX https://courses.edx.org/courses/course-v1:GTx+ISYE6501x+2T2020a/courseware/1fded79c7c304e148942f8f027c8716b/83d8d14b794f4dbfb6b201f4f944f417/?ac… 2/30 Information for Question 1 There are eight questions labeled "Question 1." Answer all eight questions. For each of the following eight questions, select the type of problem that the model is best suited for. For each question there may be more than one correct answer; you need only choose one. Each type of problem might be used zero, one, or more than one time in the eight questions. Question 1 0.5/0.5 points (graded) Select the type of problem that ARIMA is best suited for. There may be more than one correct answer; you need only choose one. You have used 1 of 1 attempt Question 1 0.5/0.5 points (graded) Select the type of problem that k-nearest-neighbor is best suited for. There may be more than one correct answer; you need only choose one. ClassiÕcation Clustering Experimental design Prediction from feature data Prediction from time-series data Variable selection [Show More]
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