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Classification in Data Mining MCQs | Classification in Data Mining Multiple Choice Questions and Answers

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Questions
1 The problem of finding hidden structure in unlabeled data is called
A Supervised learning
B Unsupervised learning
C Reinforcement learning
D None of these

Answer: Unsupervised learning
2 Some telecommunication company wants to segment their customers into distinct groups in order to send appropriate subscription offers, this is an example of
A Supervised learning
B Data extraction
C Serration
D Unsupervised learning

Answer: Unsupervised learning
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3 Self-organizing maps are an example of
A Unsupervised learning
B Supervised learning
C Reinforcement learning
D Missing data imputation

Answer: Unsupervised learning
4 In the example of predicting number of babies based on storks’ population size, number of babies is
A outcome
B feature
C attribute
D observation

Answer: outcome
5 Which of the following issue is considered before investing in Data Mining?
A Functionality
B Vendor consideration
C Compatibility
D All of the above

Answer: All of the above
6 SET concept is used in
A Network Model
B Hierarchical Model
C Relational Model
D None of these

Answer: None of these
7 Data independence means
A Data is defined separately and not included in programs
B Programs are not dependent on the physical attributes of data
C Programs are not dependent on the logical attributes of data
D Both (B) and (C)

Answer: Both (B) and (C)
8 A definition or a concept is if it classifies any examples as coming within the concept
A Complete
B Consistent
C Constant
D None of these

Answer: Consistent
9 A definition of a concept is if it recognizes all the instances of that concept
A Complete
B Consistent
C Constant
D None of these

Answer: Complete
10 Black boxes are
A This takes only two values. In general, these values will be 0 and 1 and they can be coded as one bit
B The natural environment of a certain species
C Systems that can be used without knowledge of internal operations
D None of these

Answer: Systems that can be used without knowledge of internal operations
11 Data mining is
A The actual discovery phase of a knowledge discovery process
B The stage of selecting the right data for a KDD process
C A subject-oriented integrated time variant non-volatile collection of data in support of management
D None of these

Answer: The actual discovery phase of a knowledge discovery process
12 E-R model uses this symbol to represent weak entity set?
A Dotted rectangle
B Diamond
C Doubly outlined rectangle
D None of these

Answer: Doubly outlined rectangle
13 In a relation
A Ordering of rows is immaterial
B No two rows are identical
C (A) and (B) both are true
D None of the above

Answer: (A) and (B) both are true
14 Key to represent relationship between tables is called
A Primary key
B Secondary Key
C Foreign Key
D None of these

Answer: Foreign Key
15 ________ produces the relation that has attributes of Ri and R2
A Cartesian product
B Difference
C Intersection
D Product

Answer: Cartesian product
16 Classification accuracy is
A A subdivision of a set of examples into a number of classes
B Measure of the accuracy, of the classification of a concept that is given by a certain theory
C The task of assigning a classification to a set of examples
D None of the above

Answer: Measure of the accuracy, of the classification of a concept that is given by a certain theory
17 Biotope are
A This takes only two values. In general, these values will be 0 and 1 and they can be coded as one bit
B The natural environment of a certain species
C Systems that can be used without knowledge of internal operations
D None of these

Answer: The natural environment of a certain species
18 Cluster is
A Group of similar objects that differ significantly from other objects
B Operations on a database to transform or simplify data in order to prepare it for a machine-learning algorithm
C Symbolic representation of facts or ideas from which information can potentially be extracted
D None of these

Answer: Group of similar objects that differ significantly from other objects
19 You are given data about seismic activity in Japan, and you want to predict a magnitude of the next earthquake, this is in an example of
A Supervised learning
B Unsupervised learning
C Serration
D Dimensionality reduction

Answer: Supervised learning
20 Assume you want to perform supervised learning and to predict number of newborns according to size of storks’ population (http://www.brixtonhealth.com/storksBabies.pdf), it is an example of
A Classification
B Regression
C Clustering
D Structural equation modeling

Answer: Regression
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