Data Warehousing & Data Mining bits

1. Which of the following is the most popularly available and rich information repositories?

a. Temporal databases

b. Relational databases

c. Transactional databases d. spatial databases

2. Which of the following databases is used to store time-related data?

a. Spatial databases b. Text databases

c. Multimedia databases

d. Temporal databases

3. From a DWH perspective, data mining can be viewed as an advanced stage of

a. On-Line Transaction Processing b. On-Line Data Processing

c. On-Line Analytical Processing

d. On-Line Electronic Processing

4. A _ _ _ _ _ _ is a group of heterogeneous databases?

a. Time series databases

b. Object oriented databases

c. Legacy databases

d. Spatial databases

5. Spatial databases includes

a. Legacy databases

b. Time series databases

c. Satellite image databases

d. Temporal databases

6. Many people treat data mining as synonym for another popularly used term            a. Knowledge Discovery in databases

b. knowledge inventory in databases

c. Knowledge acceptance in databases d. knowledge disposal in databases.

7. A database is a collection of

a. Related data

b. Interrelated data

c. Irrelevant data d. Distributed data

8. A Relational database is a collection of

a. tables

b. events

c. attributes d. values

9. A _ _ _ _ _ _ _ is a repository of information collected from multiple squares stored under a unified schema, and which usually resides at a single site.

a. Data mining b. Database

c. Data warehouse

d. legacy databases

10. Which of the following databases is used to store image, audio, and video data?

a. Heterogeneous databases b. Temporal databases

c. Legacy databases

d. Multimedia databases

11. What is the single dimensional association rule for the following predicate notation, which in multidimensional association rule. Contains(T, "computer") == contains(T, "software")

a. Computer == software

 b. Software == computer

c. Software == computer

d. Computer == software

12. Which of the following analysis attempt to identify attributes that do not contribute to the classification or prediction process?

a. Cluster analysis b. Outlier analysis

c. Relevance analysis

d. Evolution analysis

13. Which of the following is a summarization of the general characteristics or features of a target class of data?

a. Data discrimination

b. Data characterization

c. Data compression

d. Meta data

14. _ _ _ _ _ _ _ is a comparison of the general features of target class data objects with general features of objects from one or a set of contrasting classes.

a. Data characterization

b. Data summarization

c. Data discrimination

d. Meta data

15. _ _ _ _ _ _ _ interestingness measures are based on user beliefs in the data.

a. Objective

b. Descriptive c. Collective

d. Subjective

16. _ _ _ _ _ _ mining tasks characterize the general properties of the data in the databases.

a. Descriptive

b. Predictive c. Metadata d. Data

17. _ _ _ _ _ mining tasks perform inference on the current data in order to make predictions.

a. Descriptive b. Predictive c. Data

d. Metadata

18. The derived model may be represented in the form of

a. ER model b. Flow chart

c. Decision trees

d. DFD

19. Which of the following is the classification of data mining systems?

a. Summarization b. Visualization c. Discrimination

d. Characterization

20. _ _ _ _ _ _ _ analysis describes and models regularities or trends for objects whose behavior changes over time.

a. Data evolution

b. Cluster

c. Outlier

d. Summarization

21. Which of the following issues relation to the diversity of database type?

a. Handling noisy or incomplete data

b. Incorporation of background knowledge

c. Handling of relational and complex types of data

d. Efficiency and scalability of data mining algorithms

22. Which of the following is not major issue in data mining?

a. Mining methodology and user interaction issues

b. Performance issues

c. Issues relating to the diversity of database types

d. Issues relating to the Measurement

23. Processing _ _ _ _ _ queries in operational databases would substantially degrade the performance of operational tasks.

a. On-Line Transaction Processing b. On-Line Electronic Processing

c. On-Line Data Processing

d. On-Line Analytical Processing

24. An _ _ _ _ _ _ System typically adopts either a star or snow flake model and subject oriented database design.

a. On-Line Transaction Processing b. On-Line Electronic Processing

c. On-Line Analytical Processing

d. On-Line Data Processing

25. The access patterns of an _ _ _ _ system consist mainly of short, atomic transactions.

a. On-Line Analytical Processing

b. On-Line Transaction Processing

c. On-Line Electronic Processing d. On-Line Data Processing

26. Which of the following approach requires complex information filtering and integration processes and competes for resources with processing at local sources?

a. Update-driven approach

b. Integrate-driven approach

c. Query-driven approach d. Data-driven approach

27. Mining different kinds of knowledge in databases is an issue in

a. Performance issue

b. Mining methodology and user interaction issues

c. Diversity of database types issues d. time complexity

28. Pattern evolution is an issue related to

a. Mining methodology and user interaction issues

b. Performance issues

c. Issues relating to the diversity of database types d. Issues relating to the Measurement

29. A DWH is a subject oriented, integrated, time- variant, and _ _ _ _ _ _ collection of data in support of management's decision-making process.

a. Nonvolatile

b. Volatile

c. Disintegrated

d. Object- oriented

30. An _ _ _ system focuses mainly on the current data with in an enterprise or department, without referring to historical data or data in different organizations .

a. On-Line Analytical Processing

b. On-Line Data Processing

c. On-Line Electronic Processing

d. On-Line Transaction Processing

31. The basic characteristic of On-line Analytical Processing is a. Informational processing

b. Operational processing c. Data processing

d. Data cleaning

32. Which of the following cuboid that holds the highest level of summerization?

a. Cuboid

b. Base cuboid

c. Non-base cuboid

d. Apex coboid

33. _ _ _ _ _ _ _ _ _ _ is a visualization operation that rotates the data axes in view in order to provide an alternative presentation of the data

a. Rollup

b. Drill down

c. Pivot

d. Slice & dice

34. _ _ _ _ _ _ tables can be specified by users or experts, or automatically generated and adjusted based on data distributions.

a. Fact

b. Summarized c. Dimension d. Relational

35. _ _ _ _ _ _ _ executes queries involving more than one fact table

a. Drill-through b. Drill-across c. Drill-down

d. Rotate

36. A _ _ _ _ _ allows data to be modeled and viewed in multiple dimensions.

a. Meta data b. Data cube c. Database d. Fact table

37. The major difference between the snowflake and star schema models is that the dimension tables of the snowflake model image kept in _ _ _ _form

a. Standard

b. De-normalized

c. Normalized

d. Multi dimensional

38. Which of the following is not a measure, which is based on the kind of aggregation functions used.

a. Cumulative b. Distributed c. Algebraic

d. Holistic

39. A concept hierarchy that is a total or partial order among attributes in database schema is called a _ _ _ _ _ _ _ _ _ _ _ hierarchy.

a. Set-grouping b. Grouping

c. Decision

d. Schema

40. Which of the following focuses on socioeconomic applications?

a. Statistical database systems

b. Online Analytical Processing systems c. Spatial database systems

d. Temporal database systems

41. A _ _ _ _ _ _ _ _ _ model consists of radial lines emanating from a central point, where each line represents a concept hierarchy for a dimension

a. Cube net

b. Triangle net c. Square net d. Star net

42. Which of the following is constructed where the enterprise warehouse is the sole custodian of all warehouse data. Which is then distributed to the various dependent data marts.

a. Enterprise DWH

b. Two- tier DWH

c. Multi-tier DWH

d. Virtual warehouse

43. Which of the following is a Multi Dimensional Online Analytical Processing?

a. Ess base

b. Database

c. Swiss base d. Red brick

44. The _ _ _ _ _ _ view includes fact tables and dimension tables.

a. DWH

b. Top-down

c. Data source

d. Business Query

 45. Which of the following is a Hybrid OLAP server?

a. MS SQL server 1.0 b. MS SQL 5.0

c. MS SQL server 7.0

d. MS SQL server 3.0

46. ETL stands for

a. Evaluate, Transport and Link b. Extract Transfer and Load c. Error, Tracking and Load

d. Extract, Transient and Load

47. To architect the DWH, the major driving factor to support is

a. An inability to cope with requirements evolution b. Not populating the warehouse

c. Day- to- day management of the warehouse

d. Supporting Online Transaction processing

48. A _ _ _ _ _ _ _ contains a subset of corporate-wide data that is of value to a specific group of users.

a. Enterprise warehouse b. Virtual warehouse

c. Data warehouse

d. Data mart

49. A _ _ _ _ _ _ _ is a set of views over operational databases

a. Enterprise warehouse

b. Virtual warehouse

c. Data warehouse d. Data mart

50. What kind of the intermediate servers that stand in between a relational back-end server and client front-end tools?

a. Hybrid OLAP servers

b. Multidimensional OLAP server c. Relational OLAP servers

d. Specialized SQL servers

51. Choose the _ _ _ _ _ _ _ _ _ that will populate each fact table record a. Measures

b. Dimensions c. Grain

d. Business Process

53. Meta data repository contains

a. Operational meta data

b. Data irrelevant to system performance

c. The mapping from the DWH to the operational environment d. Summarized data

54. Which of the following support the bitmap indices

a. Sybase IQ

b. Oracle 7 c. CoBoL

d. SQL

55. _ _ _ _ _ _ _ are created for the data names and definitions of the given warehouse

a. Data cube

b. Summarized data

c. Meta data

d. Detailed Information

56. Chunking technique involves "overlapping" some of the aggregation computations, it is referred to as _ _ _ _ _ aggregation in data cube computation

a. Two way array

b. Three way array c. Multi way array d. Sparse array

57. The _ _ _ _ _ _ _ operator computes aggregates over all subsets of the dimensions specified in the operation.

a. Data base

b. Computer cube

c. Define cube

d. Group by

58. Which of the following is a subcuge that is small enough to fit into the memory available for cube computation?

a. Bulk b. Array

c. Structure

d. Chunk

59. The bit mapped join indices method is an integrated form of

a. Composite join indexing and bitmap indexing b. Join indexing and composite join indexing

c. Join indexing and bitmap indexing

d. Bitmap indexing and outer join indexing

60. A set of attributes in a relation schema that forms a primary key for another relation schema is called a _ _ _ __ _ _

a. Primary key

b. Foreign key

c. Secondary key d. Composite key

61. Which of the following typically gathers data from multiple, heterogeneous, and external sources?

a. Data cleaning b. Load

c. Refresh

d. Data extraction

62. OLAM is particularly important for the following reason

a. How quality of data in DWH

b. Data processing

c. OLTP-based exploratory data analysis

d. Online selection of data mining functions

63. Which of the following sets a good example for interactive data analysis and provides the necessary preparations for exploratory data mining?

a. OLP

b. OLAP c. OLTP d. OLDP

64. Which of the following is not exception indicator?

a. Out Expb. Self Exp c. In Exp

d. Path Exp

65. _ _ _ _ _ _ _ _ _ can help business managers find and reach more suitable customers, as well as gain critical business insights that may help to drive market share and raise profits.

a. Data warehouse

b. Data mining

c. Data summarization d. Data processing

66. _ _ _ _ _ _ _ _ _ _ _ is an alternative approach in which pre-computed measures indicating data exceptions are used to guide the user in the data analysis process at all levels of aggregation.

a. Hypothesis-driven exploration b. Inventory-driven exploration

c. Discovery-driven exploration

d. Exception-driven exploration

67. Which of the following is an exception indicator that indicates that indicates the degree of surprise of the cell value, relative to other cells at the same level of aggregation?

a. Out Exp b. In Exp

c. Path Exp

d. Self Exp

 

68. _ _ _ _ _ is a powerful paradigm that integrates OLAP with data mining technology.

a. Online Analytical Modeling b. Online Analytical Machine c. Online Analytical Mining

d. Online Analytical Monitoring

69. Data warehouse application is _ _ _ _ _ _ _ _ _

a. Data Processing

b. Transaction Processing c. Datacube

d. Datamining

70. _ _ _ _ _ _ _ _ _ cubes compute complex queries involving multiple dependent aggregates as multiple granularities

a. Multi feature

b. Data

c. Meta

d. Solid

71. Which of the following performs a linear transformation on the original data?

a. Z-score normalization

b. Normalization with decimal scaling c. Zero-standard deviation

d. Min-max normalization

72. Which of the following is the best method for missing values in data cleaning?

a. Fill in the missing value manually

b. Use the most probable value to fill in the missing value

c. Use the attribute mean to fill the missing value

d. Use a global constant to fill in the missing value

73. The minimum and maximum values in a given bin are identified as the

a. Bin means b. Bin average c. Bin medians

d. Bin boundaries

74. Which of the following is data transformation operation?

a. Normalization

b. Regression c. Clustering d. Binning

76. _ _ _ _ _ methods smooth a sorted data value by consulting in neighborhoodie the values around it.

a. Clustering

b. Binning

c. Regression

d. Data reduction

77. Z-score normalization is also called as

a. Min-max normalization

b. Zero-standard deviation normalization

c. Zero-mean normalization

d. Normalization by decimal scaling

78. _ _ _ _ _ _ is a random error or variance in a measured variable.

a. Bin

b. Cluster

c. Noise

d. Regression

79. The data are consolidated into forms appropriate for mining is called as

a. Data reduction

b. Data Redundancy c. Data clean

d. Data transformation

80. Which of the following is a decision tree algorithm?

a. C3.2 b. ID3 c. PP2 d. DIM

81. If the tuples in D are grouped into M mutually disjoint Clustering, then an simple random sample of m clusters can be obtained, where m M which of the following suits the above sentence?

a. Stratified sample

b. SRS without replacement

c. Cluster sample

d. SRS with replacement

82. Multidimensional index trees include

a. A- trees b. T-trees c. P-trees d. R-trees

83. Which of the following strategy for data reduction is irrelevant, weakly relevant, or redundant attributes may be detected and removed?

a. Data cube aggregation b. Dimension reduction c. Data compression

d. Numerosity reduction

84. In database systems, _ _ _ _ _ are primarily used for providing fast data access.

a. Red-black trees b. Game trees

c. Multidimensional index trees

d. splay trees

85. If the mining task is classification, and the mining algorithm itself is used to determine the attribute subset,then this is called a _ _ _ _ _ _ approach.

a. Filter

b. Reduction c. Smoothing d. Wrapper

86. The discrete wavelet transformation is closely related to the _ _ _ _ _ _ _transform.

a. Discrete fourier

b. Fourier c. Laplace d. wavelet

87. Principal components analysis is also called as

a. Karhunen-loeve method

b. Kinen-liva method

c. Kruskal-learn method d. Kutni-lara method

88. _ _ _ _ _ _ can be used as a data reduction technique since it allows a large data set to be represented by a much smaller random subset of the data.

a. Clustering b. Regression c. Histograms d. Sampling

89. Loy-linear models are a. Parametric methods

b. Discrete methods

c. Non-parametric methods d. Non- discrete methods

90. Which of the following method is the generation of concept of hierarchies for categorical data?

a. Specification of a portion of a hierarchy by implicit data grouping b. Specification of their partial ordering, but not

of a set of attributes

c. Specification of a set of attributes, but not of their partial order

d. Specification of only a partial set of entities

 

91. Which of the following method uses class information?

a. Histogram analysis b. Binning

c. Cluster analysis

d. Entropy-based Discretization

92. _ _ _ _ _ _ _ _ _ hierarchies for categorical attributes or dimensions typically involve a group of attributes

a. Diccretization b. Semantic

c. Index

d. Concept

93. Which of the following is based on the maximal asset values, which may lead to a highly biased hierarchy?

a. Cluster analysis b. Segmentation c. Binning

d. Histogram analysis

94. The _ _ _ _ _ can be used to segment numeric data into relatively uniform, "natural" intervals.

a. 1-2-3 rule b. 2-3-4 rule c. 3-4-5 rule d. 4-5-6rule

95. _ _ _ _ _ _ _ _ hierarchies for numeric attributes can be constructed automatically based on data distribution analysis

 a. Concept

b. Discretization c. Tree

d. Index

96. _ _ _ _ _ _ _ techniques can be used to reduce the number of values for a given continuous attribute, by dividing the range of the attribute into intervals

a. Concept hierarchy

b. Discretization

c. Tree-based d. Index

97. A _ _ _ _ _ _ _ _ _ algoithm can be applied to partition data into groups

a. Binning

b. Histogram

c. Clustering

d. Entropy-based

98. An information-based measure called _ _ _ _ can be used to recursively partition the values of a numeric attribute A, resulting in a hierarchical discretization.

a. Entropy

b. Cluster c. Binning

d. Segmentation

99. The kinds of knowledge include

a. Image analysis b. Query process c. Association

d. Multimedia analysis

100. Which of the following is a simplicity measure?

a. Rule strength b. Rule quality

c. Rule reliability

d. Rule length

101. _ _ _ _ _ _ hierarchies can be used to refine or enrich schema defined hierarchies. When the two types of hierarchies are combined.

a. Schema

b. Set-grouping

c. Operation-derived d. rule-based

102. _ _ _ _ _ _ _ are those that contribute new information or increased performance to the given pattern set.

a. Utility patterns

b. Certainty patterns

c. Novelty pattern

d. Simplicity patterns

103. Certainty factor is also known as

a. Rule length

b. Noice threshold c. Minable view

d. Rule strength

104. Which of the following primitive specifies the data mining functions to be performed?

a. Task-relevant data

b. The kind of knowledge to be mined

c. Background knowledge

d. Interestingness measures

105. _ _ _ _ _ _ _ may be used to guide the mining process or, after discovery to evaluate the discovered patterns.

a. Task-relevant data

b. The kind of knowledge to be mined c. Background knowledge

d. Interestingness measures

106. A _ _ _ _ _ hierarchy is a total or partial order among attributes in the database schema.

a. Schema

b. Set-grouping

c. Operation-derived d. rule-based

108. _ _ _ _ _ hierarchies include the decoding of information encoded strings information extraction from complex data objects and data clustering.

a. Rule-based

b. Operation-derived

c. Schema

d. Set grouping

110. Which of the following clause is the task-irrelevant data primitive?

a. In relevance to

b. Use for warehouse c. Analysis

d. Order by

111. Mining with the use of _ _ _ _ , allows additional flexibility for ad hoc rule mining.

a. Image patterns b. Data patterns

c. Information patterns

d. Meta patterns

112. Which of the following clause lists the attributes or dimensions for exploration

a. Order by b. group by c. having

d. in relevance to

113. Which of the following clause uses the meta pattern?

a. Analyze

b. In relevance to

c. Matching

d. Use data warehouse

114. Which of the following clause is used for discrimination?

a. Mine characteristics b. Mine discriminant

c. Mine association

d. Mine comparison

 115. DMQL expansion is

a. Data Modeling Queue Level

b. Design Modeling Query language

c. Data Mining Query Language

d. Data &Meta data Query Language

116. The _ _ _ _ _ clause, when used for characterization, specific aggregate measures, such as count, sum or count.

a. Use database

b. Analyze

c. Matching

d. Use hierarchy

117. Which of the following clause specifies the condition by which groups of data are considered relevant?

a. Having

b. Group by c. Order by d. analyze

118. The _ _ _ _ _ _ _ _ statement is used to specify the kind of knowledge to be mined.

a. Knowledge-mine-specification

b. Mine-knowledge-specification

c. Knowledge-specification-mine d. Specification-mine-knowledge

120. CRISP-DM addresses an issue as

a. Mapping from datamining problems to business issues b. Capturing and misunderstanding the data

c. Disintegrating datamining results within the business context

d. Deploying and maintaining data mining results

121. An Example of a set-grouping hierarchy is

a. Define hierarchy age-hierarchy for age as customer on level1:{young, middleaged, serior} level10:all level2:{20 39}

level1: young level2:{20 59}

level1: middle-aged level2:{60 89} level1:senior

b. Define hierarchy age-hierarchy as age for customer on level1:{young, middleaged, serior} level10:all level2:{20 39}

level1: young level2:{20 59}

level1: middle-aged level2:{60 89} level1:senior

c. Define hierarchy age-hierarchy for age on customer as level1:{young, middle-aged,serior} level10:all level2:{2039} level1: young level2:{20 59} level1: middle-aged level2:{60 89} level1:senior

d. Define hierarchy age-hierarchy on age for customer as level1:{young, middleaged, serior} level10:all level2:{20 39}

level1: young level2:{20 59}

level1: middle-aged level2:{60 89} level1:senior

122. Which of the following data mining language uses SQL-like syntax and serves as rule generation queries for mining association rules.

a. MINE RULE operator b. RULE MINE operator c. DATA MINE operator d. DWH operator

123. Which of the following is not a data mining language?

a. DMQL b. MSQL c. PSQL

d. OLE DB for

124. System of schema hierarchy is

a. textbf{Define hierarchy} location-hierarchy textbf{on} address textbf{as} [street, city, country]

b. textbf{Define hierarchy} location-hierarchy textbf{as} address textbf{on} [street, city, country]

c. textbf{Define hierarchy} location-hierarchy textbf{from} address textbf{to}

[street, city, country]

d. textbf{Define hierarchy }location-hierarchy textbf{for} address textbf{all} [street, city, country]

125. The DMQL statement syntax is

a. display as result _ from

b. display result _ from

c. display on result _ from d. display for result _ from

126. Which of the following is a data mining query language

a. PSQL b. QSQL c. MSQL d. RSQL

127. _ _ _ _ _ is used for efficient implementations of a few essential data mining primitives.

a. No coupling

b. Loose coupling c. Tight coupling

d. Semi tight coupling

128. _ _ _ _ _ _ _ is a compromise between loose and tight coupling.

a. No coupling

b. Loose coupling c. Tight coupling

d. Semi tight coupling

129. Which of the following coupling schema is used to fetch data from a data repository managed by database systems?

a. No coupling b. Loose coupling

c. Tight coupling

d. Semi tight coupling

130. A well designed data mining system should offer _ _ _ _ _ _ _ with a data warehouse system

a. Semi tight coupling

b. No coupling

c. Loose coupling d. Normal coupling

131. Which of the following is difficult to achieve high scalability and good performance with large data sets?

a. No coupling

b. Tight coupling

c. Semi tight coupling

d. Loose coupling

132. _ _ _ _ _ _ _ _ means that a Data mining system will not utilize any function of a data warehouse system

a. Loose coupling

b. Semi tight coupling c. Loose coupling

d. No coupling

133. _ _ _ _ _ _ _ _ means that a data mining system is smoothing integrated coupling database system.

a. No coupling

b. Loose coupling

c. Tight coupling

d. Semi tight coupling

134. Which of the following provides a concise and succinct summarization of the given collection of data?

a. Comparison

b. Characterization

c. Summerization

d. Aggregation

135. _ _ _ _ _ _ _ _ data mining describes the data set in a concise and summerative manner and presents interesting general properties of the data.

a. Descriptive

b. Predictive c. Active

d. Constructive

136. _ _ _ _ _ _ data mining analyzes the data in order to construct one or a set of models and attempts to predict thebehavior of new data sets.

a. Descriptive b. Predictive c. Active

d. Constructive

137. Attribute removal is based on the following rule: If there is a large set of distinct values for an attribute of the initial working relation but,

a. There is generalization operator on the attribute

b. There is no generalization operand on the attribute

c. There is no generalization operator on the attribute

d. There is no aggregation operator on the attribute

138. On-line analysis processing in data warehouses is a purely-controlled process

a. Machine b. database c. Developer

d. User

139. Which of the following approach is used to control generalization process?

a. Generalized relation threshold control

b. Generalized class threshold control

c. Generalized dimension threshold control d. Generalized query threshold control

140. Many current OLAP systems confine dimensions to _ _ _ _ _ _ _ _ _ _ data

a. Numeric

b. Non numeric

c. Meta

d. Summerized

141. _ _ _ _ _ _ _ is a process that abstracts a large set of task-relevant data in a database from a relatively low

conceptual level to higher conceptual levels.

a. Data realization

b. Data characterization

c. Data summerization

d. Data generalization

142. The _ _ _ _ _ _ approach can be considered as a data warehouse-based pre-computation-oriented, material view approach.

a. Object-oriented induction

b. Data cube

c. Attribute-oriented induction d. Data square

143. Which of the following approach is a relational database query-oriented, generalization-based, on-line data analysis technique?

a. Attribute-oriented induction

b. object-oriented approach c. Data cube

d. Data square

144. _ _ _ _ _ _ _ _ performs off-line aggregation before an OLAP or Data mining query is submitted for processing.

a. Object-oriented induction

b. Data cube

c. Attribute-oriented induction d. Data square

146. How can the t-weight and interestingness measures in general be used by the data mining system to display only the concept descriptions that it objectively evaluates as interesting?

a. By threshold

b. By generalization c. By comparison

d. By characterization

147. The data cube implementation of attribute-oriented induction can be performed by

a. Using defined data cube

b. Using a predefined data cube c. Using a generalized data cube d. Using a quantified data cube

148. A _ _ _ _ _ can be represented by a 3-D data cube.

a. Cross-tab

b. Bar chart

c. pie chart

d. Flow chart

149. Step one of the attribute-oriented-induction algorithm is essentially a relational query to collect the task relevant data into the _ _ _ _ _ _ _ _ _ _ .

a. Prime relation

b. Secondary relation c. Working relation d. Analyzing relation

150. Which of the following relation collects the statistics of attribute oriented induction algorithm?

a. Working relation

b. Prime relation

c. Secondary relation d. Analyzingrealation

151. Descriptions can also be visualized in the form of _ _ _ _ _ _ _ _ .

a. Cross-ralations b. Cross-checks

c. Cross-boards

d. Cross-tabs

152. Step three of attribute-oriented-induction derives the _ _ _ _ _ _ _ relation.

a. Working

b. Prime

c. Secondary d. Analysing

153. The _ _ _ _ _ _ as an interestingness measure that describes the typically of each disjoint in the rule, or of each tuple in the corresponding generalized relation.

a. Quantitative rule

b. Quantitative characteristic rule c. c-weight

d. t-weight

154. The information gain is obtained by

a. Expected information + entropy

b. Entropy - Expected information

c. Expected information entropy

d. Entropy Expected information

155. The expected information needed to classify a given sample is

a. I(s1,s2----.sm)= mathop Sigma limits_{i = 1}n ( /s) ( /s)

b. I(s1,s2----.sm)= ( /s) ( /s)

c. I(s1,s2----.sm)= - mathop Sigma limits_{i = 1}n ( /s) ( /s)

d. I(s1,s2----.sm)=- mathop Sigma limits_{i = 1}n ( /s) ( /s)

156. Class comprarison is also called as

a. composition b. aggregation

c. discrimination

d. characterization

157. _ _ _ _ _ _ can be used to perform some preliminary relevance analysis on the data by removing or generalizing attributes having a very large number of distinct values.

a. Object-oriented induction

b. Attribute-oriented induction

c. Batch-oriented induction d. Class-oriented induction

158. Class characterization that includes the analysis of attribute/dimensions relevance is called _ _ _ _ _ .

 a.Analytical comparison

b. Analytical measurement

c. Analytical characterization

d. Analytical difference

159. _ _ _ _ _ _ _ irrelevant and weakly relevant attributes using the selected relevance analysis measure.

a. Insert

b. Update c. Modify

d. Remove

160. The _ _ _ _ _ class is the class to be characterized

a. base

b. target

c. contrasting d. sub

161. The _ _ _ _ _ _ class is the set of comparable data that are not in the target class.

a. base b. target

c. contrasting

d. sub

162. Generalization is performed on the _ _ _ _ _ _ _ _ to the level controlled by a user or expert-specified dimension threshold, which results in a _ _ _ __ _ _

a. Target class, Prime target class relation

b. Contrasting class, Prime contrasting class relation

c. Target class, Secondary target class relation

d. Contrasting class, Secondary contrasting class relation

163. Let be a generalized tuple, and be the target class, the d-weight is defined as

a. d-weight =condition( ) / count( )

b. d-weight =condition( ) / mathop Sigma limits_{i = 1}m count( )

c. d-weight =condition( ) / count( )

d. d-weight =condition( ) / count( )

164. Can class comparison mining be implemented efficiently using data cube techniques?

a. yes

b. no

c. limited d. difficult

165. Class discrimination is also called as

a. class comparison

b. class hierarchy

c. class aggregation d. class concept

166. The set of relevant data in the database is collected by query processed and is partitioned respectively into a target class and one or a set of _ _ _ _ _ class(es)

a. discrimination

b. contrasting c. comparable d. target

167. The range for the d-weight is

a. b. c.

d.

168. A _ _ _ _ _ _ d-weight in the target class indicates that the concept represented by the generalized tuple is primarily derived from the target class

a. Low

b. High

c. Average d. Middle

169. A _ _ _ _ _ _ d-weight implies that the concept is primarily derived from the contrasting class

a. Low

b. High

c. Average d. Middle

170. A quantitave discriminant rule for the target class of a given comparison description is written in the form

a. x, target _ class(x) compare(x) [d: d-weight]

b. x, contrasting _ class(x) condition(x) [d: d-weight]

c. x, contrasting _ class(x) compare(x) [d: d-weight]

d. x, target _ class(x) condition(x) [d: d-weight]

171. In d-weight, d stands for

a. divide b. dead

c. discrimination

d. degree

172. Inter quartile is defined as

a. First quartile -Third quartile b. First quartile + Third quartile c. Third quartile + First quartile

d. Third quartile - First quartile

173. One common rule of thumb for identifying suspected outliers is to single out values falling at least _ _ _ _ _ __ above the third quartile or below the first quartile.

a. b. c. d.

174. The most commonly used percentiles other the median are _ _ _ _ _ _

a. Outliers b. Boxplots c. Quartiles d. Modes

175. A popularly used visual representation of a distribution is the _ _ _ _ _ _ _ _

a. Boxplot

b. Outlier c. Quartile

d. Histogram

176. Dispersion is also called as

a. Mean

b. Variance

c. Median d. mode

177. Which of the following is central tendency measure?

a. Outliers b. Variance c. Quartiles

d. Mode

178. Which of the following is a data dispersion measure?

a. Mean

b. Variance

c. Mode

d. Median

179. The average of the largest and smallest values in a data set is called as

a. Median b. Mean

c. Mid range

d. Mode

180. The _ _ _ _ _ _ _ _ for a set of data is the value that occurs most frequently in the set.

a. Median b. Mean

c. Mid range

d. Mode

181. Which of the following is not central tendency measure?

a. Variance

b. Mean

c. Median d. Mode

182. A _ _ _ _ _ _ _ _ is one of the most effective graphical methods or trend between two quantitative variables.

a. q-q plot

b. scatter plot c. quantile plot d. q-q-q plot

183. A _ _ _ _ _ _ _ _ is another important exploratory graphic aid that adds a smooth curve to a scatter plot in order to provide better perception of the pattern of dependence.

a. Loess curve b. Scatter curve c. Bar chat

d. Quantile plot

184. Histograms are also called as _ _ _ _ _ _ _ _ _ histograms. a. frequency

b. variance c. quartile d. outlier

185. The word loess is short for

a. Load compression b. Local compression c. Load refression

d. Local refression

186. A _ _ _ _ _ _ _ _ _ consists of a set of rectangles that reflect the counts of the classes present in the given data.

a. Quartile plot b. q-q plot

c. Histogram

d. Loess curves

187. A _ _ _ _ _ _ is a simple and effective way to have a first look at an unvariate data distribution.

a. q-q plot

b. scatter plot c. histogram

d. quantile plot