Data mining MCQ for RGPV (diploma)
Que-1-
Data mining is the process of finding valid, novel, useful, and
_______________, patterns in large volume of data. Which of the following terms
best fills the gap above?
A.
voluminous
B.
heterogeneous
C.
actionable
D.
noisy
Accepted Answers:
C. actionable
Que-2-
Which of the following is usually the last step in the data mining process?
A.
Visualization
B.
Preprocessing
C.
Modeling
D.
Deployment
Accepted Answers:
D. Deployment
Que-3-
Name of a movie, can
be considered as an attribute of type?
A.
Nominal
B.
Ordinal
C.
Interval
D.
Ratio
Answers:
A. Nominal
Que-4-
User rating given to
a movie in a scale 1-10, can be considered as an attribute of type?
A.
Nominal
B.
Ordinal
C.
Interval
D.
Ratio
Accepted Answers:
B. Ordinal
Que-5-
Which of the
following operations cannot be performed on interval attributes?
A.
Distinctness
B.
Order
C.
Addition
D.
Multiplication
Accepted Answers:
D. Multiplication
Que-6-
Which of the
following operations can be performed on ratio attributes?
A.
Addition
B.
Multiplication
C.
Both of the above
D.
None of the above
Answers:
C. Both of the above
Que-7-
Sales database of items
in a supermarket can be considered as an example of:
A.
Record data
B.
Tree data
C.
Graph data
D.
None of the above
Accepted Answers:
A. Record data
Que-8-
Rows of a data matrix
storing record data usually represents?
A.
Metadata
B.
Objects
C.
Attributes
D.
Aggregates
Accepted Answers:
B. Objects
Que-9-
Which of the
following is an example of continuous attribute?
A.
Weight of a person
B.
Shoe size of a person
C.
Gender of a person
D.
None of the above
Accepted Answers:
A. Weight of a person
Que-10-
If a record data
matrix has reduced number of columns after a transformation, the transformation
has performed:
A.
Data sampling
B.
Dimensionality reduction
C.
Noise cleaning
D.
Discretization
Accepted Answers:
B. Dimensionality
reduction
Que-11-
If a record data
matrix has reduced number of rows after a transformation, the transformation
has performed:
A.
Data sampling
B.
Dimensionality reduction
C.
Noise cleaning
D.
Discretization
Accepted Answers:
A. Data sampling
If a record data
matrix has reduced number of rows after a transformation, the transformation
has performed:
A.
Data sampling
B.
Dimensionality reduction
C.
Noise cleaning
D.
Discretization
Accepted Answers:
A. Data sampling
Que-12- If a supermarket has L items, the number of possible
itemsets is:
A.
2L-1
B. 2L-1
C. L/2
C. L/2
D. L-1
Accepted
Answers:
B.
2L-1
Que-13- Consider an association rule of the form A® B, where A and B are itemsets. Support of the rule is defined as:
Que-13- Consider an association rule of the form A® B, where A and B are itemsets. Support of the rule is defined as:
A. Fraction of transactions that contain both A and B
B. Fraction of transactions that contain A
C. Fraction of transactions that contain B
D. None of the above
Accepted Answers:
A. Fraction of
transactions that contain both A and B
Que-14- A store
sells 7 items. Maximum possible number of candidate 3-itemsets is:
A. 15
B. 25
C. 35
D. 45
Accepted
Answers:
C. 35
Que-15-
An itemset satisfying the
support criterion is known as:
A. Frequent itemset
B. Confident itemset
C. Accurate itemset
D. Reliable itemset
Accepted
Answers:
A.
Frequent itemset
Que-16- If A, B are two sets of items, and A⊆ B. Which of the following
statement is always true?:
A. support(A) ≤ support(B)
B. support(A) ≥ support(B)
C. support(A) = support(B)
D. support(A) ≠ support(B)
Accepted
Answers:
B. support(A) ≥
support(B)
Que-17- Consider
the itemset {A, B, C, D}. Which of the following statements is always true?
A.
confidence(ABC ® D)≥ confidence(AB ® CD)
B.
confidence(ABC ® D) ≥ confidence(AB ®D)
C. confidence(ABC ® D)
≤confidence(AB ®CD)
D. confidence(ABC ® D) ≤
confidence(AB ®D)
Accepted
Answers:
A. confidence(ABC ® D)≥
confidence(AB ® CD)
Que-18- Consider three itemsets V1 = {tomato, potato, onion}, V2
= {tomato, potato}, V3 = {tomato}. Which of the following statements are correct?
A. support(V1) > support(V2)
B. support(V3) > support(V2)
C. support(V1) > support(V3)
D. none of the above
Accepted
Answers:
B.
support(V3) > support(V2)
Que-19- In the
following data table, what is the support of the itemset {b, c}?
Transaction ID
|
Itemsets
|
1
|
{a, b, d, e}
|
2
|
{b, c, d}
|
3
|
{a, b, d, e}
|
4
|
{a, c, d, e}
|
5
|
{b, c, d, e}
|
6
|
{b, d, c}
|
7
|
{c, d}
|
8
|
{a, b, c}
|
9
|
{a, d, e}
|
10
|
{b, c}
|
A. 0.1
B. 0.3
C.
0.5
D.
0.7
Accepted
Answers:
C. 0.5
Que-20- In the
following data table, what is the confidence of the rule b®c?
Transaction ID
|
Itemsets
|
1
|
{a, b, d, e}
|
2
|
{b, c, d}
|
3
|
{a, b, d, e}
|
4
|
{a, c, d, e}
|
5
|
{b, c, d, e}
|
6
|
{b, d, c}
|
7
|
{c, d}
|
8
|
{a, b, c}
|
9
|
{a, d, e}
|
10
|
{b, c}
|
A. 2/7
B.
3/7
C.
4/7
D.
5/7
Accepted
Answers:
D. 5/7
Que-21- In the
following data table, if the support threshold is (greater than or equal to)
0.2 the frequent 4-itemsets are:
Transaction ID
|
Itemsets
|
1
|
{a, b, d, e}
|
2
|
{b, c, d}
|
3
|
{a, b, d, e}
|
4
|
{a, c, d, e}
|
5
|
{b, c, d, e}
|
6
|
{b, d, c}
|
7
|
{c, d}
|
8
|
{a, b, c}
|
9
|
{a, d, e}
|
10
|
{b, c}
|
A. {a, b, c, d}
B.
{a, b, c, e}
C. {a, c, d, e}
D. {a, b, d, e}
Accepted
Answers:
D. {a, b, d, e}
Que-22- In the
following data table, if the support threshold is (greater than or equal to)
0.2, and confidence threshold is (greater than or equal to) 0.9, valid
association rules are:
Transaction ID
|
Itemsets
|
1
|
{a, b, d, e}
|
2
|
{b, c, d}
|
3
|
{a, b, d, e}
|
4
|
{a, c, d, e}
|
5
|
{b, c, d, e}
|
6
|
{b, d, c}
|
7
|
{c, d}
|
8
|
{a, b, c}
|
9
|
{a, d, e}
|
10
|
{b, c}
|
A. {a,b,d} ® e
B. {a, b}®{d, e}
C. a®{b, d, e}
D. b ®{a, d, e}
Accepted
Answers:
A.
{a,b,d} ® e
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