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Which tree is the least complex and contains the smallest validation error?


A) best-pruned tree
B) full-grown tree
C) minimum error tree
D) categorical tree

E) A) and B)
F) A) and C)

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Robin wanted to know if the age partition chosen for her data was the best fit for her 30 case, 90% Class 1, 10% Class 0 partition. She completed the Gini impurity index with the results of (Age < 32) = 0.2034 and (Age ≥\ge 32) = 0.2786. What is the weighted combination and what did partition at Age 32 produce?


A) Robin was able to reduce the Gini index from 0.2786 to 0.2507, confirming the best split for age.
B) Robin was able to reduce the Gini index from 0.2786 to 0.20, confirming the best split for age.
C) Robin was able to reduce the Gini index from 0.2786 to 0.2109, confirming the best split for age.
D) Robin realized with the 0.2507 weighted average, the age split was not the best split for the age range.

E) All of the above
F) B) and D)

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Decision trees produced by the CART algorithm are binary, meaning that there are two branches for each decision node.

A) True
B) False

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True

Using the following pruning table, which tree is the minimum error tree? Using the following pruning table, which tree is the minimum error tree? A) Level 3 B) Level 2 C) Level 1 D) Additional Levels needed to identify minimum tree among candidate trees.


A) Level 3
B) Level 2
C) Level 1
D) Additional Levels needed to identify minimum tree among candidate trees.

E) B) and C)
F) None of the above

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Based on the following values for income, what are the possible split points? {12,665, 15,432, 28,763, 34,876, 43,987, 53,677}


A) {14048.5, 22097.5, 31819.5, 39431.5, 48832, 53677}

B) {12665, 14048.5, 22097.5, 31819.5, 39431.5, 48832}

C) {14048.5, 22097.5, 31819.5, 39431.5, 48832}

D) {14048, 22097, 31819, 39431, 48832}

E) B) and D)
F) A) and D)

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If 80% of the cases belong to Class 0 and 20% belong to Class 1, what is the Gini index?


A) 0.32
B) 0
C) 0.40
D) 0.16

E) All of the above
F) A) and B)

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In a R complexity parameter table, the xerror column represents:


A) the cross-validation errors associated with each candidate tree.
B) the recommended measure for the full tree.
C) the maximum error point for the first node split.
D) the root node type argument point.

E) All of the above
F) None of the above

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Based on the following sorted 20 values for age, what are the possible split points? {20, 22, 24, 26, 28, 31, 32, 34, 35, 40, 42, 43, 45, 47, 49, 51, 52, 53, 55, 57}


A) {20, 21, 23, 25, 27, 29.5, 31.5, 33, 34.5, 37.5, 41, 42.5, 44, 46, 48, 50, 51.5, 52.5, 54, 56}

B) {21, 23, 25, 27, 29.5, 31.5, 33, 34.5, 37.5, 41, 42.5, 44, 46, 48, 50, 51.5, 52.5, 54, 56, 57}

C) {0, 21, 23, 25, 27, 29.5, 31.5, 33, 34.5, 37.5, 41, 42.5, 44, 46, 48, 50, 51.5, 52.5, 54, 56}

D) {21, 23, 25, 27, 29.5, 31.5, 33, 34.5, 37.5, 41, 42.5, 44, 46, 48, 50, 51.5, 52.5, 54, 56}

E) None of the above
F) B) and C)

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Based on the Gini index, 0.10 implies a higher degree of purity because it is closer to 0 than 0.5.

A) True
B) False

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Using the following pruning table, which tree is the best-pruned tree? Using the following pruning table, which tree is the best-pruned tree? A) Level 3 B) Level 2 C) Level 1 D) Additional Levels needed to identify best-pruned tree.


A) Level 3
B) Level 2
C) Level 1
D) Additional Levels needed to identify best-pruned tree.

E) A) and C)
F) B) and C)

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A

The following table reflects a partial Analytic Solver's Performance measure for a hotel cost during an NFL game night. What is the MAD implying? The following table reflects a partial Analytic Solver's Performance measure for a hotel cost during an NFL game night. What is the MAD implying? A) The predicted mean absolute deviation is 0.51 of the mean absolute percentage error. B) The predicted cost is relatively low, providing the need for full tree. C) The predicted average cost is lesser than the standard error, thus impure. D) The predicted cost on average differs from the actual cost by $50.56.


A) The predicted mean absolute deviation is 0.51 of the mean absolute percentage error.
B) The predicted cost is relatively low, providing the need for full tree.
C) The predicted average cost is lesser than the standard error, thus impure.
D) The predicted cost on average differs from the actual cost by $50.56.

E) B) and D)
F) A) and B)

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When a target variable is categorical, the CART algorithm produces a __________ tree to predict the class memberships of new cases.


A) classification
B) regression
C) minimum
D) pruned

E) A) and D)
F) C) and D)

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The following table reflects a partial Analytic Solver's Performance measure for a hotel cost during an NFL game night. What is the MAD implying? The following table reflects a partial Analytic Solver's Performance measure for a hotel cost during an NFL game night. What is the MAD implying? A) The predicted mean absolute deviation is 0.53 of the mean absolute percentage error. B) The predicted cost is relatively low, providing the need for full tree. C) The predicted average cost is lesser than the standard error, thus impure. D) The predicted cost on average differs from the actual cost by $52.56.


A) The predicted mean absolute deviation is 0.53 of the mean absolute percentage error.
B) The predicted cost is relatively low, providing the need for full tree.
C) The predicted average cost is lesser than the standard error, thus impure.
D) The predicted cost on average differs from the actual cost by $52.56.

E) A) and B)
F) None of the above

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D

The overall MSE split for Age = 25 is $22,987,111.29 and for Age = 23 is $21,983,723.40. Of the two presented, Age = 25 is slightly higher and has a lower level of impurity for constructing a regression tree.

A) True
B) False

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A split at the $32,000 Income point creates a top and bottom partition. Compute the overall (weighted) Gini index given an Income Split of $32,000. A split at the $32,000 Income point creates a top and bottom partition. Compute the overall (weighted) Gini index given an Income Split of $32,000. A) MSE<sub>split</sub> <sub>(</sub><sub>Income=$36,000</sub><sub>) </sub> = 0.2667 B) MSE<sub>split</sub> <sub>(</sub><sub>Income=$36,000</sub><sub>) </sub> = 0.0000 C) MSE<sub>split</sub> <sub>(</sub><sub>Income=$36,000</sub><sub>) </sub> = 0.4959 D) MSE<sub>split</sub> <sub>(</sub><sub>Income=$36,000</sub><sub>) </sub> = 0.3637


A) MSEsplit (Income=$36,000) = 0.2667
B) MSEsplit (Income=$36,000) = 0.0000
C) MSEsplit (Income=$36,000) = 0.4959
D) MSEsplit (Income=$36,000) = 0.3637

E) C) and D)
F) A) and D)

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Using the following sample of a regression prune log, the minimum error tree is decision node # 19 with a standard error of 4.689492 (not shown) . Using the information provided, which decision node number represents the best-pruned tree? Using the following sample of a regression prune log, the minimum error tree is decision node # 19 with a standard error of 4.689492 (not shown) . Using the information provided, which decision node number represents the best-pruned tree? A) decision node #21 B) decision node #5 C) decision node #4 D) decision node #17


A) decision node #21
B) decision node #5
C) decision node #4
D) decision node #17

E) B) and C)
F) A) and D)

Correct Answer

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Viewing the results in the following scatterplot, for the 11 cases to the left subset (Age < 40) , two belong to Class 1 and nine belong to Class 0. In the right subset (Age ? 40) three belong to Class 1 and one belong to Class 0. What is the Index score for the two subsets? Viewing the results in the following scatterplot, for the 11 cases to the left subset (Age < 40) , two belong to Class 1 and nine belong to Class 0. In the right subset (Age ? 40) three belong to Class 1 and one belong to Class 0. What is the Index score for the two subsets? A) (Age < 40) = 0.3636; (Age \ge 40) = 0.50 B) (Age < 40) = 0.20; (Age \ge 40) = 0.25 C) (Age < 40) = 0.298; (Age \ge 40) = 0.375 D) (Age < 40) = 0.375; (Age \ge 40) = 0.298


A) (Age < 40) = 0.3636; (Age ≥\ge 40) = 0.50
B) (Age < 40) = 0.20; (Age ≥\ge 40) = 0.25
C) (Age < 40) = 0.298; (Age ≥\ge 40) = 0.375
D) (Age < 40) = 0.375; (Age ≥\ge 40) = 0.298

E) A) and B)
F) None of the above

Correct Answer

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The overall MSE split for Age = 24 is $21,987,111.29 and for Age = 23 is $20,983,723.40. Of the two presented, Age = 24 is slightly higher and has a lower level of impurity for constructing a regression tree.

A) True
B) False

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Before constructing a decision tree, one of the first steps is identifying possible splits of the predictor variable.

A) True
B) False

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A pure subset contains leaf nodes where cases have contradicting values to the target variable, to enhance the variable case outcomes and allow for further splits.

A) True
B) False

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