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dules Multiple Attempts Not allowed. This test can only be taken once. Force Completion This test can be saved and resumed at any point until
dules Multiple Attempts Not allowed. This test can only be taken once. Force Completion This test can be saved and resumed at any point until time has expired. The timer wil Your answers are saved automatically. kshops Remaining Time: 44 minutes, 01 second. . Assigns entation * Question Completion Status: on Moving to another question will save this response. Question 1 Consider following dataset of 3 inputs and a target variable. ources a XXXr le 1 1 1 1 1 21 10 1 3 1 0 1 0 41 0 0 0 Given the above data set. The expected entropy EH of X2 variable is. Note: EH(X) = Expected Entropy of subsets of X when it is split on target Y. 0.55 0 0.82 O 0.42 O 0.65 A Moving to another question will save this response.Remaining Time: 35 minutes, 14 seconds. Question Completion Status: Moving to another question will save this response. Question 4 a x XXr 123g X e It 1 1 1 1 1 21 10 1 310 10 4 10 0 0 50 1 10 Construct a consistent decision tree given the above data set. A. The root node of the tree is B. Examples processed at root node C. Examples processed at level 2 D. Which variable is not included in the decision tree. O A. X2 , B. 5 , C. 3 D. X3 A. X2 , B. 2 , C. 5 D. X1 A. X2 , B. 5 , C. 3 D. X1 A. X2 , B. 2 , C. 5 D. X3 O A. X1 , B. 5 , C. 3 D. X2Moving to another question will save this response. Question 3 Consider following dataset of 3 inputs and a target variable. a xxxr d 12 3 g le It 11 1 1 1 21 10 1 3 4 10 0 0 15 01 10 Given the above data set. The expected entropy EH of X1 variable is. Note: EH(X) = Expected Entropy of subsets of X when it is split on target Y. O 0.75 0.65 O 0.2 0.80 K > Moving to another question will save this response.Question Completion Status: Moving to another question will save this response. Question 5 Consider the follosing dataset. la xxxr 1 2 3 g e x le 1 1 1 1 1 21 10 1 3101 1 4 1 0 0 0 50 1 10 Given the above data set. Calculate A. H(Target) --> the Entropy of Target B. EH(X1 | Target) --> the Expected/Conditional Entropy of X1 given Target. C. IG(X1) --> Information Gain of X1 A. 0.92 , B. 0.46 , C. 0.46 A. 0.97 , B. 0.46, C. 0.73 A. 0.97 , B. 0.73 , C. 0.46 O A. 0.97, B. 0.64 , C. 0.32 Moving to another question will save this response.Take Test: Quiz 3 Test Information Description Instructions Timed Test This test has a time limit of 45 minutes, This test will save and submit automatically when the time expires. Warnings appear when half the time, 5 minutes, 1 minute, and 30 seconds remain. Multiple Attempts Not allowed. This test can only be taken once. Force Completion This test can be saved and resumed at any point until time has expired. The timer will continue to run If you le Your answers are saved automatically. Remaining Time: 33 minutes, 11 seconds. * Question Completion Status: Moving to another question will save this response. Question 6 Consider this code to distinguish the elements of a set (a, b, c, d}, with P(a) = 0.5, P(b)=0.25, P(c)=0.125 and P(d)=0.125. a. 0 b. 10 C. 110 d. 111 On average, a sequence made up of a, b, c, d will use how many bits. 1.75 O 2.7 0 3 1.05 Moving to another question will save this response.Question Completion Status: Moving to another question will save this response. Question 2 Consider following dataset of 3 inputs and a target variable. la x xxr e 1 2 3 g e x 1 1 1 1 1 21 101 31010 4 10 0 0 50 1 10 Given the above data set. The expected entropy EH of X3 variable is. Note: EH(X) = Expected Entropy of subsets of X when it is split on target Y. O 0.55 O 0.82 O 0.65 0 0.95 A Moving to another question will save this response
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