Data Mining and Business Intelligence (2170715) MCQs

MCQs of Concept Description and Association Rule Mining

Showing 1 to 10 out of 17 Questions
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1.

A collection of one or more items is called as _____

(a)

Itemset
(b)

Support
(c)

Confidence 
(d)

Support Count
Answer:

Option (a)

2.

Frequency of occurrence of an itemset is called as _____

(a)

Support
(b)

Confidence
(c)

Support Count
(d)

Rules
Answer:

Option (c)

3.

An itemset whose support is greater than or equal to a minimum support threshold is ______

(a)

Itemset
(b)

Frequent Itemset
(c)

Infrequent items
(d)

Threshold values
Answer:

Option (b)

4.

What does FP growth algorithm do?

(a)

It mines all frequent patterns through pruning rules with lesser support
(b)

It mines all frequent patterns through pruning rules with higher support
(c)

It mines all frequent patterns by constructing a FP tree
(d)

It mines all frequent patterns by constructing an itemsets
Answer:

Option (c)

5.

What techniques can be used to improve the efficiency of apriori algorithm?

(a)

Hash-based techniques
(b)

Transaction Increases 
(c)

Sampling
(d)

Cleaning
Answer:

Option (a)

6.

What do you mean by support(A)?

(a)

Total number of transactions containing A
(b)

Total Number of transactions not containing A
(c)

Number of transactions containing A / Total number of transactions
(d)

Number of transactions not containing A / Total number of transactions
Answer:

Option (c)

7.

How do you calculate Confidence (A -> B)?

(a)

Support(A ∩ B) / Support (A)
(b)

Support(A ∩ B) / Support (B)
(c)

Support(A ∪ B) / Support (A)
(d)

Support(A ∪ B) / Support (B)
Answer:

Option (a)

8.

Which of the following is the direct application of frequent itemset mining?

(a)

Social Network Analysis
(b)

Market Basket Analysis
(c)

Outlier Detection
(d)

Intrusion Detection
Answer:

Option (b)

9.

What is not true about FP growth algorithms?

(a)

It mines frequent itemsets without candidate generation
(b)

There are chances that FP trees may not fit in the memory
(c)

FP trees are very expensive to build
(d)

It expands the original database to build FP trees
Answer:

Option (d)

10.

When do you consider an association rule interesting?

(a)

If it only satisfies min_support
(b)

If it only satisfies min_confidence
(c)

If it satisfies both min_support and min_confidence
(d)

There are other measures to check so
Answer:

Option (c)

Showing 1 to 10 out of 17 Questions
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