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Question 7 (1 point) Consider a decision tree constructed for a classification problem, where the possible classes are A , B and C . How

Question 7 (1 point)

Consider a decision tree constructed for a classification problem, where the possible classes are A, B and C. How many branches does an arbitrary internal node in the decision tree have?

Question 7 options:

1

2

3

4

it varies, depending on what attribute the node branches on

Question 8 (1 point)

info([a, b]) =

Question 8 options:

entropy(-a, -b)

entropy(a, b)

entropy(a/(a+b), b/(a+b))

entropy(-a/(a+b), -b/(a+b))

-(a/(a+b))entropy(a/(a+b)) - (b/(a+b))entropy(b/(a+b))

Question 9 (1 point)

Consider the process of constructing a decision tree based on the training set in Table 1 and using the information gain algorithm discussed in class. What is the information gain when branching at the root of the decision tree on the attribute Aquatic?

Table 1: Vertebrate Dataset (modified from Introduction to Data Mining by Tan et al.)

Name

Body temp

Give birth

Aquatic

Class

human

warm

yes

no

mammal

echidna

warm

no

no

mammal

salmon

cold

no

yes

fish

whale

warm

yes

yes

mammal

eel

cold

no

yes

fish

bat

warm

yes

no

mammal

shark

cold

yes

yes

fish

cat

warm

yes

no

mammal

Question 9 options:

(1/2)info([4,0]) + (1/2)info([1,3])

info([5,3]) (1/2)info([4,0]) (1/2)info([1,3])

(5/8)info([1,4]) + (3/8)info([3,0])

info([5,3]) (5/8)info([1,4]) (3/8)info([3,0])

none of the above

Question 10 (1 point)

If we are going to build a decision tree for the dataset in Table 1, which attribute (not considering Name) will be selected as the root?

Table 1: Vertebrate Dataset (modified from Introduction to Data Mining by Tan et al.)

Name

Body temp

Give birth

Aquatic

Class

human

warm

yes

no

mammal

echidna

warm

no

no

mammal

salmon

cold

no

yes

fish

whale

warm

yes

yes

mammal

eel

cold

no

yes

fish

bat

warm

yes

no

mammal

shark

cold

yes

yes

fish

cat

warm

yes

no

mammal

Question 10 options:

Body temp

Give birth

Aquatic

one of Give birth or Aquatic, since it is a tie, randomly pick one

any of the three attributes

Question 11 (1 point)

When the decision tree built from the previous question is used on the test instance in Table 2, what is the predicted class for porcupine?

Table 2: Test Instance

Name

Body temp

Give birth

Aquatic

Class

porcupine

warm

yes

no

?

Question 11 options:

mammal

fish

cannot decide

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