Data Mining and Business Intelligence (2170715) MCQs

MCQs of Concept Description and Association Rule Mining

Showing 11 to 17 out of 17 Questions
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11.

What is the relation between a candidate and frequent itemsets?

(a)

A candidate itemset is always a frequent itemset
(b)

A frequent itemset must be a candidate itemset
(c)

No relation between these two
(d)

Strong relation with transactions 
Answer:

Option (b)

12.

Which of the following is not a frequent pattern mining algorithm?

(a)

Apriori
(b)

FP growth
(c)

Decision trees
(d)

Eclat
Answer:

Option (c)

13.

Which algorithm requires fewer scans of data?

(a)

Apriori
(b)

FP Growth
(c)

Naive Bayes
(d)

Decision Trees
Answer:

Option (b)

14.

For the question given below consider the data Transactions :

  1. I1, I2, I3, I4, I5, I6
  2. I7, I2, I3, I4, I5, I6
  3. I1, I8, I4, I5
  4. I1, I9, I10, I4, I6
  5. I10, I2, I4, I11, I5

With support as 0.6 find all frequent itemsets?

(a)

<I1>, <I2>, <I4>, <I5>, <I6>, <I1, I4>, <I2, I4>, <I2, I5>, <I4, I5>, <I4, I6>, <I2, I4, I5>
(b)

<I2>, <I4>, <I5>, <I2, I4>, <I2, I5>, <I4, I5>, <I2, I4, I5>
(c)

<I11>, <I4>, <I5>, <I6>, <I1, I4>, <I5, I4>, <I11, I5>, <I4, I6>, <I2, I4, I5>
(d)

<I1>, <I4>, <I5>, <I6>
Answer:

Option (a)

15.

What will happen if support is reduced?

(a)

Number of frequent itemsets remains the same
(b)

Some itemsets will add to the current set of frequent itemsets
(c)

Some itemsets will become infrequent while others will become frequent
(d)

Can not say
Answer:

Option (b)

16.

What is association rule mining?

(a)

Same as frequent itemset mining
(b)

Finding of strong association rules using frequent itemsets
(c)

Using association to analyze correlation rules
(d)

Finding Itemsets for future trends
Answer:

Option (b)

17.

A definition or a concept is ______ if it classifies any examples as coming within the concept

(a)

Concurrent
(b)

Consistent
(c)

Constant
(d)

Compete 
Answer:

Option (b)

Showing 11 to 17 out of 17 Questions
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