Are you a student gearing up for an upcoming exam and desperately seeking comprehensive on Data Mining MCQ Multiple Choice Questions with accurate answers to help you ace your exam in 2023?
Look no further, as you have stumbled upon the right place! In this article, we will provide you with a wide range of MCQs specifically tailored for Data Mining, enabling you to sharpen your knowledge and enhance your chances of success.
Whether you are a beginner or already well-versed in the subject matter, these questions will serve as a valuable resource to gauge your understanding and test your grasp on key concepts in Data Mining. So let’s dive into the realm of multiple choice questions and prepare ourselves thoroughly for the challenges that lie ahead!
Top 110 Data Mining MCQs with answers
1. Information can be converted into knowledge about ___ patterns and future trends.
2. Data about data is called ___.
3. Facts, numbers, or text is called ___.
4. ___ and ___ are the key to emerging Business Intelligence technologies.
Ans: Data warehouse and data mining
5. Data mining is also called ___.
Ans: Knowledge discovery
6. Online Analytical Processing (OLAP) is a technology that is used to create ___ software.
Ans: Decision support
7. OLAP Supports ___ user access and multiple queries.
8. Statistics techniques are incorporated into Data mining methods. (True/False).
9. ___ Optimization techniques are based on the concepts of genetic combination, mutation, and natural selection.
Ans: Genetic algorithms
10. What is Mineset?
Ans: MineSet is software that provides tools for searching, sorting, filtering and drilling down enabling previously complex data models to be viewed intuitively through real-time 3-D graphical representation.
11. A data warehouse refers to a database that is maintained separately from an organization’s operational databases. (True/False)
12. A data warehouse is usually constructed by integrating multiple heterogeneous sources. (True/False)
13. ___ system is customer-oriented and is used for transaction and query processing by clerks, clients, and information technology professionals.
14. A ___ allows data to be modelled and viewed in multiple Dimensions.
Ans: Data cube
15. In ___ schema some dimension tables are normalized, thereby further splitting the data into additional tables.
16. The ___ data model is commonly used in the design of relational databases.
17. Data warehouses and OLAP tools are based on ___ data model.
18. The ___ exposes the information being captured, stored, and managed by operational systems.
Ans: Data source view
19. ___ are the intermediate servers that stand in between a relational back – end server and client front – end tools.
Ans: Relational OLAP (ROLAP) servers
20. A ___ is a set of views over operational databases.
Ans: Virtual warehouse
21. The ___ software gives the user the opportunity to look at the data from a variety of different dimensions.
Ans: Multidimensional Analysis
22. Which of the following statements defines Business Intelligence?
A. Converting data into knowledge and making it available throughout the organization
B. Analytical software and solutions for gathering, consolidating, analyzing and providing access to information in a way that is supposed to let the users of an enterprise make better business decisions.
C. Both A & B
Ans: C. Both A & B
23. Based on the overall requirements of business intelligence, the ___ layer is required to extract, cleanse and transform data into load files for the information warehouse.
Ans: Data integration
24. Data Mining is not a business solution; it is just a technology. (True/False)
25. ___ is a random error or variance in measured variables.
26. State true or false
I. BI applications can also help managers to be better informed about actions that a company’s competitors are taking
II. BI can help companies share selected strategic information with business partners.
III. BI 2.0″ is used to describe the acquisition, provision and analysis of “real-time” data
A. i-T, ii-F, iii-F
B. i-T, ii-T, iii-F
C. i-T, ii-F, iii-T
D. i-T, ii-T, iii-T
27. ___ routines attempt to fill in missing values, smooth out noise while identifying outlines, and correct inconsistencies in the data.
Ans: Data cleaning
28. ___ is used to refer to systems and technologies that provide the business with the means for decision-makers to extract personalized meaningful information about their business and industry.
Ans: Business Intelligence
29. In ___ each value in a bin is replaced by the mean value of the bin.
Ans: Smoothing by bin means
30. ___ regression involves finding the “best” line to fit two variables so that one variable can be used to predict the other.
31. ___ works to remove the noise from the data that includes techniques like binning, clustering, and regression.
32. Redundancies can be detected by correlation analysis. (True/False)
33. The ___ technique uses encoding mechanisms to reduce the data set size.
Ans: Data compression
34. In which Strategy of data reduction redundant attributes are detected.
A. Date cube aggregation
B. Numerosity reduction
C. Data compression
D. Dimension reduction
Ans: D. Dimension reduction
35. ___ hierarchies can be used to reduce the data by collecting and replacing low-level concepts by higher-level concepts.
36. The ___ rule can be used to segment numeric data into relatively uniform, “natural” intervals.
37. Oracle, SQL/Server, DB2 are examples for ___.
38. Data Base Management System (DBMS) supports query languages. (True/False)
39. The ___ item sets find all sets of items (items sets) whose support is greater than the user-specified minimum support, σ.
Ans: Frequent set
40. A frequent set is a ___ if it is a frequent set and no superset of this is a frequent set.
Ans: Maximal frequent set
41. ___ techniques are used to detect relationships or associations between specific values of categorical variables in large data sets.
Ans: Association rule mining
42. A Decision Tree is a ___ model.
Ans: Predictive model
43. Using a decision tree, only categorical variables would be modelled. (True/False).
44. Clustering is an unsupervised learning method (True/false).
45. Neural networks are made up of many ___.
Ans: Artificial neurons
46. For a given transaction database T, a ___ is an expression of the form X => Y, where X and Y are subsets of A and X => Y holds with confidence Ʈ, if Ʈ% of transactions in D support X also support Y.
Ans: Association rule
47. The ___ rule describes associations between quantitative items or attributes.
Ans: Quantitative association
48. The ___ step eliminates the extensions of (k-1) – itemsets, which are not found to be frequent, from being considered for counting support.
49. In the first phase of the Partition algorithm, the algorithm logically divides the database into a number of ___.
Ans: non – overlapping partitions.
50. The a priori algorithm operates in a ___ and ___.
Ans: bottom-up, breadth-first search method.
51. ___ algorithm works like a train running over the data, with stops at intervals M between transactions. When the train reaches the end of the transaction file it completes one path.
Ans: DIC Algorithm
52. FP–Tree Growth Algorithm can be implemented in ___ Phases.
53. FP – tree stands for ___.
Ans: Frequent pattern tree
54. Data mining systems should provide capabilities to mine association rules at multiple levels of abstraction and traverse easily among different abstraction spaces (True/False).
55. Which one of the following is alternative search strategies for mining multiple-level associations with reduced support?
a) Level – by level independent
b) Level – cross-filtering by a single item
c) Level – cross-filtering by k – itemset:
d) All the above
Ans: d) All the above
56. Which of the following is NOT a common binning strategy?
a) Equiwidth binning,
b) Equidepth binning,
c) Homogeneity – based binning,
d) Equilength binning
Ans: d) Equilength binning
57. Association rules that involve two or more dimension or predicates can be referred to as ___.
Ans: Multidimensional association rules.
58. An algorithm that performs a series of “walks” through itemset space is called a ___.
Ans: Random walk algorithm.
59. What are knowledge type constraints?
Ans: They specify the type of knowledge to be mined.
60. A standard measure of within-cluster similarity is ___.
61. The process of grouping a set of physical or abstract objects into classes of similar objects is called ___.
62. Clustering may also be considered as ___.
63. Clustering is also called:
c. Partitions with similar objects
d. All the above
Ans: d. All the above
64. Clustering is used only in data mining (True/False).
65. Clustering is a form of learning by observation rather than ___.
Ans: By example
66. Weight and height of an individual fall into ___ kind of variables.
67. In the K-means algorithm for partitioning, each cluster is represented by the ___ of objects in the cluster.
68. K-means clustering requires prior knowledge about number clusters required as its input.(True/False).
69. One form of unsupervised learning is ___.
70. ___ software provides a set of partitioned clustering algorithms that treat the clustering problem as an optimization process.
71. Data classification is a ___ step process.
72. ___ can be viewed as the construction and use of a model to assess the class of an unlabeled sample, or to assess the value or value ranges of an attribute that a given sample is likely to have.
73. ___ of data removes or reduces noise (by applying smoothing techniques) and the treatment of missing values.
74. ___ method refers to the ability to construct the model efficiently given a large amount of data.
75. What is a decision tree?
Ans: This is a flow – chart – like a tree structure, where each internal node denotes a test on an attribute, each branch represents an outcome of the test, and leaf nodes represent classes or class distributions.
76. The basic algorithm for decision tree induction is a ___ algorithm.
77. The ___ measure is used to select the test attribute at each node in the tree.
Ans: information gain
78. A user session is a ___ record spanning the entire Web.
Ans: Clickstream record
79. ___ is simple text files that are automatically generated every time someone accesses one Website.
Ans: Log File
80. ___ files are frequently used in sequential mining.
Ans: Web log files
81. ___ is used to examine the structure of a particular website and collate and analyze related data.
Ans: Structural mining
82. Which of the following techniques are concerned about user navigation accessing?
a. Web structural mining
b. Web usage mining
c. Web content mining
d. Web data definition mining
Ans: b. Web usage mining
83. Web data is ___.
a. Structured data
b. Un-structured data
c. Only text data
d. Binary data
Ans: b. Un-structured data
84. ___ Web mining involves the development of Sophisticated Artificial Intelligence systems.
Ans: an agent-based approach
85. The ___ approaches to Web mining have generally focused on techniques for integrating and organizing the heterogeneous and semi-structured data on the Web into more structured and high-level collections of resources.
86. Association rules involving multimedia objects can be mined in ___ and ___ databases.
Ans: Image and video
87. In ___ approach, the signature of an image includes color histograms based on the color composition of an image regardless of its scale or orientation.
Ans: Color histogram-based signature
88. Which of the following are the measures of the text retrieval documents?
Ans: d. a,b,c
89. Data stored in most text databases are ___.
90. Which of the following is the first step in text retrieval systems?
b. Term words finding
d. Replacing the null data with keywords
Ans: c. Tokenization
91. Which of the following are the stop words?
Ans: d. a,b,c
92. Text databases are also called ___.
Ans: Document databases
93. Insurance and direct mail are two industries that rely on ___ to make profitable business decisions.
Ans: data analysis
94. To aid decision-making, analysts construct ___ models using warehouse data to predict the outcomes of a variety of decision alternatives.
95. A ___ profile is a model that predicts the future purchasing behaviour of an individual customer, given historical transaction data for both the individual and for the larger population of all of a particular company’s customers.
96. Data mining can be used to help predict future patient behaviour and to improve treatment programs (True/False).
98. Data mining in the telecommunication industry helps to understand the business involved, identify telecommunication patterns (True/False).
99. GDP stands for ___.
Ans: gross domestic product
100. ___ is proving to be a critical link between theory, simulation, and experiment.
Ans: data-intensive computing
101. IDS are based on ___ that are developed by the manual encoding of expert knowledge.
Ans: Handcrafted signatures
102. Choose the correct option.
Data mining can be used to improve ___.
b) Quality of data
d) All the above
Ans: D. All the above.
103. To improve accuracy, data mining programs are used to analyze audit data and extract features that can distinguish normal activities from intrusions. (True/False)
104. Data mining-based IDSs (especially anomaly detection systems) have higher false-positive rates than traditional handcrafted signature-based methods. (True/False)
105. ___ is a new class of intrusion detection algorithms that do not rely on labelled data.
Ans: Unsupervised anomaly detection
106. ___ algorithm uses the frequency distribution of each feature’s values to proportionally generate a sufficient amount of anomalies.
Ans: Distribution Based Artificial Anomaly
107. OLAP typically includes the following kinds of analyses: simple, comparison, trend, ___ and ___.
Ans: Variance and ranking
108. Patient Rule Induction Method (PRIM) and Weighted Item Sets (WIS), is a type of ___ technique.
Ans: Association rule
109. ___ tools cannot discover high average regions or find new patterns in data.
110. ___ method is useful for finding patterns or associations between attributes.
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