McqMate
1. |
Adaptive system management is |
A. | it uses machine-learning techniques. here program can learn from past experience and adapt themselves to new situations. |
B. | computational procedure that takes some value as input and produces some value as output. |
C. | science of making machines performs tasks that would require intelligence when performed by humans. |
D. | none of these |
Answer» A. it uses machine-learning techniques. here program can learn from past experience and adapt themselves to new situations. |
2. |
Bayesian classifiers is |
A. | a class of learning algorithm that tries to find an optimum classification of a set of examples using the probabilistic theory. |
B. | any mechanism employed by a learning system to constrain the search space of a hypothesis. |
C. | an approach to the design of learning algorithms that is inspired by the fact that when people encounter new situations, they often explain them by reference to familiar experiences, adapting the explanations to fit the new situation. |
D. | none of these |
Answer» A. a class of learning algorithm that tries to find an optimum classification of a set of examples using the probabilistic theory. |
3. |
Algorithm is |
A. | it uses machine-learning techniques. here program can learn from past experience and adapt themselves to new situations. |
B. | computational procedure that takes some value as input and produces some value as output. |
C. | science of making machines performs tasks that would require intelligence when performed by humans. |
D. | none of these |
Answer» B. computational procedure that takes some value as input and produces some value as output. |
4. |
Bias is |
A. | a class of learning algorithm that tries to find an optimum classification of a set of examples using the probabilistic theory. |
B. | any mechanism employed by a learning system to constrain the search space of a hypothesis. |
C. | an approach to the design of learning algorithms that is inspired by the fact that when people encounter new situations, they often explain them by reference to familiar experiences, adapting the explanations to fit the new situation. |
D. | none of these |
Answer» B. any mechanism employed by a learning system to constrain the search space of a hypothesis. |
5. |
Background knowledge referred to |
A. | additional acquaintance used by a learning algorithm to facilitate the learning process. |
B. | a neural network that makes use of a hidden layer. |
C. | it is a form of automatic learning. |
D. | none of these |
Answer» A. additional acquaintance used by a learning algorithm to facilitate the learning process. |
6. |
Case-based learning is |
A. | a class of learning algorithm that tries to find an optimum classification of a set of examples using the probabilistic theory. |
B. | any mechanism employed by a learning system to constrain the search space of a hypothesis. |
C. | an approach to the design of learning algorithms that is inspired by the fact that when people encounter new situations, they often explain them by reference to familiar experiences, adapting the explanations to fit the new situation. |
D. | none of these |
Answer» C. an approach to the design of learning algorithms that is inspired by the fact that when people encounter new situations, they often explain them by reference to familiar experiences, adapting the explanations to fit the new situation. |
7. |
Classification is |
A. | a subdivision of a set of examples into a number of classes. |
B. | a 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 these |
Answer» A. a subdivision of a set of examples into a number of classes. |
8. |
Binary attribute 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» A. this takes only two values. in general, these values will be 0 and 1 and .they can be coded as one bit |
9. |
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 these |
Answer» B. measure of the accuracy, of the classification of a concept that is given by a certain theory. |
10. |
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» B. the natural environment of a certain species |
11. |
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» A. group of similar objects that differ significantly from other objects |
12. |
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» C. systems that can be used without knowledge of internal operations |
13. |
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» A. complete |
14. |
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» B. consistent |
15. |
Data selection 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» B. the stage of selecting the right data for a kdd process |
16. |
DNA (Deoxyribonucleic acid) |
A. | it is hidden within a database and can only be recovered if one ,is given certain clues (an example is encrypted information). |
B. | the process of executing implicit previously unknown and potentially useful information from data |
C. | an extremely complex molecule that occurs in human chromosomes and that carries genetic information in the form of genes. |
D. | none of these |
Answer» C. an extremely complex molecule that occurs in human chromosomes and that carries genetic information in the form of genes. |
17. |
Hybrid is |
A. | combining different types of method or information |
B. | approach to the design of learning algorithms that is structured along the lines of the theory of evolution. |
C. | decision support systems that contain an information base filled with the knowledge of an expert formulated in terms of if-then rules. |
D. | none of these |
Answer» A. combining different types of method or information |
18. |
Discovery is |
A. | it is hidden within a database and can only be recovered if one is given certain clues (an example is encrypted information). |
B. | the process of executing implicit previously unknown and potentially useful information from data. |
C. | an extremely complex molecule that occurs in human chromosomes and that carries genetic information in the form of genes. |
D. | none of these |
Answer» B. the process of executing implicit previously unknown and potentially useful information from data. |
19. |
Euclidean distance measure is |
A. | a stage of the kdd process in which new data is added to the existing selection. |
B. | the process of finding a solution for a problem simply by enumerating all possible solutions according to some pre-defined order and then testing them |
C. | the distance between two points as calculated using the pythagoras theorem. |
D. | none of these |
Answer» C. the distance between two points as calculated using the pythagoras theorem. |
20. |
Hidden knowledge referred to |
A. | a set of databases from different vendors, possibly using different database paradigms |
B. | an approach to a problem that is not guaranteed to work but performs well in most cases |
C. | information that is hidden in a database and that cannot be recovered by a simple sql query. |
D. | none of these |
Answer» C. information that is hidden in a database and that cannot be recovered by a simple sql query. |
21. |
Enrichment is |
A. | a stage of the kdd process in which new data is added to the existing selection |
B. | the process of finding a solution for a problem simply by enumerating all possible solutions according to some pre-defined order and then testing them |
C. | the distance between two points as calculated using the pythagoras theorem. |
D. | none of these |
Answer» A. a stage of the kdd process in which new data is added to the existing selection |
22. |
Heterogeneous databases referred to |
A. | a set of databases from different b vendors, possibly using different database paradigms |
B. | an approach to a problem that is not guaranteed to work but performs well in most cases. |
C. | information that is hidden in a database and that cannot be recovered by a simple sql query. |
D. | none of these |
Answer» A. a set of databases from different b vendors, possibly using different database paradigms |
23. |
Enumeration is referred to |
A. | a stage of the kdd process in which new data is added to the existing selection. |
B. | the process of finding a solution for a problem simply by enumerating all possible solutions according to some pre-defined order and then testing them |
C. | the distance between two points as calculated using the pythagoras theorem. |
D. | none of these |
Answer» B. the process of finding a solution for a problem simply by enumerating all possible solutions according to some pre-defined order and then testing them |
24. |
Heuristic is |
A. | a set of databases from different vendors, possibly using different database paradigms |
B. | an approach to a problem that is not guaranteed to work but performs well in most cases |
C. | information that is hidden in a database and that cannot be recovered by a simple sql query. |
D. | none of these |
Answer» B. an approach to a problem that is not guaranteed to work but performs well in most cases |
25. |
Hybrid learning is |
A. | machine-learning involving different techniques |
B. | the learning algorithmic analyzes the examples on a systematic basis 2nd makes incremental adjustments to the theory that is learned |
C. | learning by generalizing from examples |
D. | none of these |
Answer» A. machine-learning involving different techniques |
26. |
Kohonen self-organizing map referred to |
A. | the process of finding the right formal representation of a certain body of knowledge in order to represent it in a knowledge-based system |
B. | it automatically maps an external signal space into a system\s internal representational space. they are useful in the performance of classification tasks |
C. | a process where an individual learns how to carry out a certain task when making a transition from a situation in which the task cannot be carried out to a situation in which the same\ task under the same circumstances can be carried out. |
D. | none of these |
Answer» B. it automatically maps an external signal space into a system\s internal representational space. they are useful in the performance of classification tasks |
27. |
Incremental learning referred to |
A. | machine-learning involving different techniques |
B. | the learning algorithmic analyzes the examples on a systematic basis and makes incremental adjustments to the theory that is learned |
C. | learning by generalizing from examples |
D. | none of these |
Answer» B. the learning algorithmic analyzes the examples on a systematic basis and makes incremental adjustments to the theory that is learned |
28. |
Knowledge engineering is |
A. | the process of finding the right formal representation of a certain body of knowledge in order to represent it in a knowledge-based system |
B. | it automatically maps an external signal space into a system\s internal representational space. they are useful in the performance of classification tasks. |
C. | a process where an individual learns how to carry out a certain task when making a transition from a situation in which the task cannot be carried out to a situation in which the same task under the same circumstances can be carried out. |
D. | none of these |
Answer» A. the process of finding the right formal representation of a certain body of knowledge in order to represent it in a knowledge-based system |
29. |
Information content is |
A. | the amount of information with in data as opposed to the amount of redundancy or noise. |
B. | one of the defining aspects of a data warehouse |
C. | restriction that requires data in one column of a database table to the a subset of another-column. |
D. | none of these |
Answer» A. the amount of information with in data as opposed to the amount of redundancy or noise. |
30. |
Inductive learning is |
A. | machine-learning involving different techniques |
B. | the learning algorithmic analyzes the examples on a systematic basis and makes incremental adjustments to the theory that is learned |
C. | learning by generalizing from examples |
D. | none of these |
Answer» C. learning by generalizing from examples |
31. |
Inclusion dependencies |
A. | the amount of information with in data as opposed to the amount of redundancy or noise |
B. | one of the defining aspects of a data warehouse |
C. | restriction that requires data in one column of a database table to the a subset of another-column |
D. | none of these |
Answer» C. restriction that requires data in one column of a database table to the a subset of another-column |
32. |
KDD (Knowledge Discovery in Databases) is referred to |
A. | non-trivial extraction of implicit previously unknown and potentially useful information from data |
B. | set of columns in a database table that can be used to identify each record within this table uniquely. |
C. | collection of interesting and useful patterns in a database |
D. | none of these |
Answer» A. non-trivial extraction of implicit previously unknown and potentially useful information from data |
33. |
Learning is |
A. | the process of finding the right formal representation of a certain body of knowledge in order to represent it in a knowledge-based system |
B. | it automatically maps an external signal space into a system\s internal representational space. they are useful in the performance of classification tasks. |
C. | a process where an individual learns how to carry out a certain task when making a transition from a situation in which the task cannot be carried out to a situation in which the same task under the same circumstances can be carried out. |
D. | none of these |
Answer» C. a process where an individual learns how to carry out a certain task when making a transition from a situation in which the task cannot be carried out to a situation in which the same task under the same circumstances can be carried out. |
34. |
Naive prediction is |
A. | a class of learning algorithms that try to derive a prolog program from examples. |
B. | a table with n independent attributes can be seen as an n- dimensional space. |
C. | a prediction made using an extremely simple method, such as always predicting the same output. |
D. | none of these |
Answer» C. a prediction made using an extremely simple method, such as always predicting the same output. |
35. |
Learning algorithm referrers to |
A. | an algorithm that can learn |
B. | a sub-discipline of computer science that deals with the design and implementation of learning algorithms. |
C. | a machine-learning approach that abstracts from the actual strategy of an individual algorithm and can therefore be applied to any other form of machine learning. |
D. | none of these |
Answer» A. an algorithm that can learn |
36. |
Knowledge is referred to |
A. | non-trivial extraction of implicit previously unknown and potentially useful information from data |
B. | set of columns in a database table that can be used to identify each record within this table uniquely |
C. | collection of interesting and useful patterns in a database |
D. | none of these |
Answer» C. collection of interesting and useful patterns in a database |
37. |
Node is |
A. | a component of a network |
B. | in the context of kdd and data mining, this refers to random errors in a database table. |
C. | one of the defining aspects of a data warehouse |
D. | none of these |
Answer» A. a component of a network |
38. |
Machine learning is |
A. | an algorithm that can learn |
B. | a sub-discipline of computer science that deals with the design and implementation of learning algorithms |
C. | an approach that abstracts from the actual strategy of an individual algorithm and can therefore be applied to any other form of machine learning. |
D. | none of these |
Answer» B. a sub-discipline of computer science that deals with the design and implementation of learning algorithms |
39. |
Projection pursuit is |
A. | the result of the application of a theory or a rule in a specific case |
B. | one of several possible enters within a database table that is chosen by the designer as the primary means of accessing the data in the table. |
C. | discipline in statistics that studies ways to find the most interesting projections of multi-dimensional spaces |
D. | none of these |
Answer» C. discipline in statistics that studies ways to find the most interesting projections of multi-dimensional spaces |
40. |
Inductive logic programming is |
A. | a class of learning algorithms that try to derive a prolog program from examples |
B. | a table with n independent attributes can be seen as an n-dimensional space |
C. | a prediction made using an extremely simple method, such as always predicting the same output |
D. | none of these |
Answer» A. a class of learning algorithms that try to derive a prolog program from examples |
41. |
Statistical significance is |
A. | the science of collecting, organizing, and applying numerical facts |
B. | measure of the probability that a certain hypothesis is incorrect given certain observations. |
C. | one of the defining aspects of a data warehouse, which is specially built around all the existing applications of the operational data |
D. | none of these |
Answer» B. measure of the probability that a certain hypothesis is incorrect given certain observations. |
42. |
Multi-dimensional knowledge is |
A. | a class of learning algorithms that try to derive a prolog program from examples |
B. | a table with n independent attributes can be seen as an n-dimensional space |
C. | a prediction made using an extremely simple method, such as always predicting the same output. |
D. | none of these |
Answer» B. a table with n independent attributes can be seen as an n-dimensional space |
43. |
Prediction is |
A. | the result of the application of a theory or a rule in a specific case |
B. | one of several possible enters within a database table that is chosen by the designer as the primary means of accessing the data in the table. |
C. | discipline in statistics that studies ways to find the most interesting projections of multi-dimensional spaces. |
D. | none of these |
Answer» A. the result of the application of a theory or a rule in a specific case |
44. |
Query tools are |
A. | a reference to the speed of an algorithm, which is quadratically dependent on the size of the data |
B. | attributes of a database table that can take only numerical values. |
C. | tools designed to query a database. |
D. | none of these |
Answer» C. tools designed to query a database. |
45. |
Operational database is |
A. | a measure of the desired maximal complexity of data mining algorithms |
B. | a database containing volatile data used for the daily operation of an organization |
C. | relational database management system |
D. | none of these |
Answer» B. a database containing volatile data used for the daily operation of an organization |
46. |
...................... is an essential process where intelligent methods are applied to extract data patterns. |
A. | data warehousing |
B. | data mining |
C. | text mining |
D. | data selection |
Answer» B. data mining |
47. |
Which of the following is not a data mining functionality? |
A. | characterization and discrimination |
B. | classification and regression |
C. | selection and interpretation |
D. | clustering and analysis |
Answer» C. selection and interpretation |
48. |
............................. is a summarization of the general characteristics or features of a target class of data. |
A. | data characterization |
B. | data classification |
C. | data discrimination |
D. | data selection |
Answer» A. data characterization |
49. |
............................. is a comparison of the general features of the target class data objects against the general features of objects from one or multiple contrasting classes. |
A. | data characterization |
B. | data classification |
C. | data discrimination |
D. | data selection |
Answer» A. data characterization |
50. |
Strategic value of data mining is ...................... |
A. | cost-sensitive |
B. | work-sensitive |
C. | time-sensitive |
D. | technical-sensitive |
Answer» C. time-sensitive |
51. |
............................. is the process of finding a model that describes and distinguishes data classes or concepts. |
A. | data characterization |
B. | data classification |
C. | data discrimination |
D. | data selection |
Answer» A. data characterization |
52. |
The full form of KDD is .................. |
A. | knowledge database |
B. | knowledge discovery database |
C. | knowledge data house |
D. | knowledge data definition |
Answer» A. knowledge database |
53. |
The out put of KDD is ............. |
A. | data |
B. | information |
C. | query |
D. | useful information |
Answer» A. data |
54. |
. The full form of OLAP is |
A. | online analytical processing |
B. | online advanced processing |
C. | online advanced preparation |
D. | online analytical performance |
Answer» C. online advanced preparation |
55. |
......................... is a subject-oriented, integrated, time-variant, nonvolatile collection or data in support of management decisions. |
A. | data mining |
B. | data warehousing |
C. | document mining |
D. | text mining |
Answer» A. data mining |
56. |
The data is stored, retrieved and updated in .................... |
A. | olap |
B. | oltp |
C. | smtp |
D. | ftp |
Answer» B. oltp |
57. |
An .................. system is market-oriented and is used for data analysis by knowledge workers, including managers, executives, and analysts. |
A. | olap |
B. | oltp |
C. | both of the above |
D. | none of the above |
Answer» A. olap |
58. |
........................ is a good alternative to the star schema. |
A. | star schema |
B. | snowflake schema |
C. | fact constellation |
D. | star-snowflake schema |
Answer» A. star schema |
59. |
The ............................ exposes the information being captured, stored, and managed by operational systems. |
A. | top-down view |
B. | data warehouse view |
C. | data source view |
D. | business query view |
Answer» C. data source view |
60. |
The type of relationship in star schema is ............... |
A. | many to many |
B. | one to one |
C. | one to many |
D. | many to one |
Answer» A. many to many |
61. |
The .................. allows the selection of the relevant information necessary for the data warehouse. |
A. | top-down view |
B. | data warehouse view |
C. | data source view |
D. | business query view |
Answer» D. business query view |
62. |
Which of the following is not a component of a data warehouse? |
A. | metadata |
B. | current detail data |
C. | lightly summarized data |
D. | component key |
Answer» C. lightly summarized data |
63. |
Which of the following is not a kind of data warehouse application? |
A. | information processing |
B. | analytical processing |
C. | data mining |
D. | transaction processing |
Answer» D. transaction processing |
64. |
Data warehouse architecture is based on ....................... |
A. | dbms |
B. | rdbms |
C. | sybase |
D. | sql server |
Answer» B. rdbms |
65. |
.......................... supports basic OLAP operations, including slice and dice, drill-down, roll-up and pivoting. |
A. | information processing |
B. | analytical processing |
C. | data mining |
D. | transaction processing |
Answer» C. data mining |
66. |
The core of the multidimensional model is the ....................... , which consists of a large set of facts and a number of dimensions. |
A. | multidimensional cube |
B. | dimensions cube |
C. | data cube |
D. | data model |
Answer» B. dimensions cube |
67. |
The data from the operational environment enter ........................ of data warehouse. |
A. | current detail data |
B. | older detail data |
C. | lightly summarized data |
D. | highly summarized data |
Answer» A. current detail data |
68. |
A data warehouse is ...................... |
A. | updated by end users. |
B. | contains numerous naming conventions and formats |
C. | organized around important subject areas |
D. | contain only current data |
Answer» A. updated by end users. |
69. |
Business Intelligence and data warehousing is used for .............. |
A. | forecasting |
B. | data mining |
C. | analysis of large volumes of product sales data |
D. | all of the above |
Answer» B. data mining |
70. |
Data warehouse contains ................ data that is never found in the operational environment. |
A. | normalized |
B. | informational |
C. | summary |
D. | denormalized |
Answer» A. normalized |
71. |
................... are responsible for running queries and reports against data warehouse tables. |
A. | hardware |
B. | software |
C. | end users |
D. | middle ware |
Answer» D. middle ware |
72. |
The biggest drawback of the level indicator in the classic star schema is that is limits ............ |
A. | flexibility |
B. | quantify |
C. | qualify |
D. | ability |
Answer» B. quantify |
73. |
............................. are designed to overcome any limitations placed on the warehouse by the nature of the relational data model. |
A. | operational database |
B. | relational database |
C. | multidimensional database |
D. | data repository |
Answer» A. operational database |
74. |
KDD describes the _________. |
A. | whole process of extraction of knowledge from data |
B. | extraction of data |
C. | extraction of information |
D. | extraction of rules |
Answer» A. whole process of extraction of knowledge from data |
75. |
SQL helps to find _______. |
A. | the interesting data |
B. | hidden information |
C. | intermediate data |
D. | data under constraints that are already known |
Answer» D. data under constraints that are already known |
76. |
Translation of problem to learning technique is called as _______. |
A. | reengineering. |
B. | translational engineering. |
C. | representational engineering. |
D. | learning algorithm. |
Answer» C. representational engineering. |
77. |
Which one of the following is not a part of empirical cycle in scientific research? |
A. | Observation |
B. | Theory. |
C. | Self learning. |
D. | Prediction. |
Answer» C. Self learning. |
78. |
________and __________ are the important qualities of good learning algorithm. |
A. | Consistent, Complete. |
B. | Information content, Complex. |
C. | Complete, Complex. |
D. | Transparent, Complex. |
Answer» A. Consistent, Complete. |
79. |
Redundancy refers to the elements of a message that can be derived from other parts of _________. |
A. | different message. |
B. | irrelevant message. |
C. | same message. |
D. | complete message. |
Answer» C. same message. |
80. |
Metadata describes __________. |
A. | contents of database. |
B. | structure of contents of database. |
C. | structure of database. |
D. | database itself. |
Answer» B. structure of contents of database. |
81. |
The partition of overall data warehouse is _______. |
A. | database. |
B. | data cube. |
C. | data mart. |
D. | operational data. |
Answer» C. data mart. |
82. |
__________ is used to load the information from operational database. |
A. | Replication technique. |
B. | Reengineering technique. |
C. | Engineering technique. |
D. | Transformation engineering. |
Answer» A. Replication technique. |
83. |
___________ multiprocessing machines share same hard disk and internal memory. |
A. | Massively parallel. |
B. | Symmetric. |
C. | Parallel. |
D. | Asymmetric. |
Answer» B. Symmetric. |
84. |
A trivial result that is obtained by an extremely simple method is called _______. |
A. | naive prediction. |
B. | accurate prediction. |
C. | correct prediction. |
D. | wrong prediction. |
Answer» A. naive prediction. |
85. |
The information on two attributes is displayed in ____________ in scatter diagram. |
A. | visualization space. |
B. | scatter space. |
C. | cartesian space. |
D. | interactive space. |
Answer» C. cartesian space. |
86. |
OLAP stands for ________. |
A. | Online Analytical Processing. |
B. | Online Linear Analytical Processing. |
C. | Online Animated Process. |
D. | Online Analytical Problem. |
Answer» A. Online Analytical Processing. |
87. |
K-nearest neighbor is one of the _______. |
A. | learning technique. |
B. | OLAP tool. |
C. | purest search technique. |
D. | data warehousing tool. |
Answer» C. purest search technique. |
88. |
The intermediate unit in perceptron is ________. |
A. | photoreceptors. |
B. | associators. |
C. | responders. |
D. | receptors. |
Answer» B. associators. |
89. |
OLAP is used to explore the ___________ knowledge. |
A. | shallow. |
B. | deep. |
C. | multidimensional. |
D. | hidden. |
Answer» C. multidimensional. |
90. |
A natural way to visualize the process of training a self-organizing map is called __________. |
A. | kohonen movie. |
B. | kohonen map. |
C. | frame. |
D. | scatter diagram. |
Answer» A. kohonen movie. |
91. |
Hidden knowledge can be found by using ________. |
A. | searching algorithm. |
B. | pattern recognition algorithm. |
C. | searching algorithm. |
D. | clues. |
Answer» B. pattern recognition algorithm. |
92. |
Deep knowledge can be found only by using ________. |
A. | clues. |
B. | OLAP. |
C. | SQL. |
D. | algorithm |
Answer» A. clues. |
93. |
The next stage to data selection in KDD process ______. |
A. | enrichment. |
B. | coding. |
C. | cleaning. |
D. | reporting. |
Answer» C. cleaning. |
94. |
Enrichment means ____. |
A. | adding external data. |
B. | deleting data. |
C. | cleaning data. |
D. | selecting the data. |
Answer» A. adding external data. |
95. |
The decision support system is used only for _______. |
A. | cleaning. |
B. | coding. |
C. | selecting. |
D. | queries. |
Answer» D. queries. |
96. |
In _________ approach data ware house is build first and all information needed is selected. |
A. | top-down. |
B. | client/server. |
C. | bottom-up. |
D. | DSS. |
Answer» A. top-down. |
97. |
The DB vendor who is able to operate massively parallel computers is ________. |
A. | TCS. |
B. | IBM. |
C. | CTS. |
D. | Wipro. |
Answer» B. IBM. |
98. |
Which of the following is closely related to statistical significance and transparency? |
A. | Classification Accuracy. |
B. | Transparency. |
C. | Statistical significance. |
D. | Search Complexity. |
Answer» B. Transparency. |
99. |
________ is a creative activity that has to be performed repeatedly in order to get best results. |
A. | Cleaning |
B. | Reporting |
C. | Coding. |
D. | Selection. |
Answer» C. Coding. |
100. |
_________ is an example for case based-learning. |
A. | Decision trees. |
B. | Neural networks. |
C. | Genetic algorithm. |
D. | K-nearest neighbor. |
Answer» D. K-nearest neighbor. |
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