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MCQOPTIONS
This section includes 347 Mcqs, each offering curated multiple-choice questions to sharpen your Computer Science Engineering (CSE) knowledge and support exam preparation. Choose a topic below to get started.
| 51. |
When objects are represented using single attribute, the proximity value 1 indicates : |
| A. | objects are similar |
| B. | objects are dissimilar |
| C. | not equal |
| D. | reflexive |
| Answer» B. objects are dissimilar | |
| 52. |
The terms equality and roll up are associated with ____________. |
| A. | olap. |
| B. | visualization. |
| C. | data mart. |
| D. | decision tree. |
| Answer» D. decision tree. | |
| 53. |
Statistics |
| 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 dat(A) |
| D. | None of these |
| Answer» B. Measure of the probability that a certain hypothesis is incorrect given certain observations. | |
| 54. |
____________ are a different paradigm for computing which draws its inspiration from neuroscience. |
| A. | computer networks. |
| B. | neural networks. |
| C. | mobile networks. |
| D. | artificial networks. |
| Answer» C. mobile networks. | |
| 55. |
Which one manages both current and historic transactions? |
| A. | oltp |
| B. | olap |
| C. | spread sheet |
| D. | xml |
| Answer» C. spread sheet | |
| 56. |
Source data from the warehouse comes from _______________. |
| A. | ods. |
| B. | tds. |
| C. | mddb. |
| D. | ordbms. |
| Answer» B. tds. | |
| 57. |
The important aspect of the data warehouse environment is that data found within the datawarehouse is___________. |
| A. | subject-oriented. |
| B. | time-variant. |
| C. | integrated. |
| D. | all of the above. |
| Answer» E. | |
| 58. |
_____ Lower when objects are more alike. |
| A. | dissimilarity |
| B. | recall |
| C. | similarity |
| D. | accuracy |
| Answer» B. recall | |
| 59. |
In ____________, the value of an attribute is examined as it varies over time. |
| A. | regression. |
| B. | time series analysis. |
| C. | sequence discovery. |
| D. | prediction. |
| Answer» C. sequence discovery. | |
| 60. |
The paths from root node to the nodes labelled 'a' are called __________. |
| A. | transformed prefix path. |
| B. | suffix subpath. |
| C. | transformed suffix path. |
| D. | prefix subpath. |
| Answer» E. | |
| 61. |
____________ maps data into predefined groups. |
| A. | regression. |
| B. | time series analysis |
| C. | prediction. |
| D. | classification. |
| Answer» E. | |
| 62. |
The ________ algorithm is based on the observation that the frequent sets are normally very few innumber compared to the set of all itemsets. |
| A. | a priori. |
| B. | clustering. |
| C. | association rule. |
| D. | partition. |
| Answer» E. | |
| 63. |
___________ is an important functional component of the metadata. |
| A. | digital directory. |
| B. | repository. |
| C. | information directory. |
| D. | data dictionary. |
| Answer» D. data dictionary. | |
| 64. |
Verification |
| A. | It does not need the control of the human operator during their execution. |
| B. | An arrow in a multi-dimensional space. It is a quantity usually characterized by an ordered set of scalars. |
| C. | The validation of a theory on the basis of a finite number of examples |
| D. | None of these |
| Answer» D. None of these | |
| 65. |
________ is data that is distilled from the low level of detail found at the current detailed leve. |
| A. | highly summarized data. |
| B. | lightly summarized data. |
| C. | metadata. |
| D. | older detail data. |
| Answer» C. metadata. | |
| 66. |
CLARANS stands for _______. |
| A. | clara net server. |
| B. | clustering large application range network search. |
| C. | clustering large applications based on randomized search. |
| D. | clustering application randomized search. |
| Answer» D. clustering application randomized search. | |
| 67. |
Data dictionary is |
| A. | Large collection of data mostly stored in a computer system |
| B. | The removal of noise errors and incorrect input from a database |
| C. | The systematic description of the syntactic structure of a specific database. It describes the structure of the attributes the tables and foreign key relationships. |
| D. | None of these |
| Answer» D. None of these | |
| 68. |
Data warehouse is based on_____________ |
| A. | two dimensional model |
| B. | three dimensional model |
| C. | multi dimensional model |
| D. | unidimensional model |
| Answer» D. unidimensional model | |
| 69. |
Reducing the number of attributes to solve the high dimensionality problem is called as ________. |
| A. | dimensionality curse. |
| B. | dimensionality reduction. |
| C. | cleaning. |
| D. | overfitting. |
| Answer» C. cleaning. | |
| 70. |
Data transformation includes __________. |
| A. | a process to change data from a detailed level to a summary level. |
| B. | a process to change data from a summary level to a detailed level. |
| C. | joining data from one source into various sources of data. |
| D. | separating data from one source into various sources of data. |
| Answer» B. a process to change data from a summary level to a detailed level. | |
| 71. |
The output of KDD is __________. |
| A. | data. |
| B. | information. |
| C. | query. |
| D. | useful information. |
| Answer» E. | |
| 72. |
________________ design involves deciding on their centres and the sharpness of their Gaussians. |
| A. | dr. |
| B. | and. |
| C. | xor. |
| D. | rbf. |
| Answer» E. | |
| 73. |
_________data consists of sample input data as well as the classification assignment for the data. |
| A. | missing. |
| B. | measuring. |
| C. | non-training. |
| D. | training. |
| Answer» E. | |
| 74. |
The _______ step eliminates the extensions of (k-1)-itemsets which are not found to be frequent,from being considered for counting support. |
| A. | candidate generation. |
| B. | pruning. |
| C. | partitioning. |
| D. | itemset eliminations. |
| Answer» C. partitioning. | |
| 75. |
Each neuron is made up of a number of nerve fibres called _____________. |
| A. | electrons. |
| B. | molecules. |
| C. | atoms. |
| D. | dendrites. |
| Answer» E. | |
| 76. |
___________can be thought of as classifying an attribute value into one of a set of possible classes. |
| A. | estimation. |
| B. | prediction. |
| C. | identification. |
| D. | clarification. |
| Answer» C. identification. | |
| 77. |
________is the most well known association rule algorithm and is used in most commercialproducts. |
| A. | apriori algorithm. |
| B. | partition algorithm. |
| C. | distributed algorithm. |
| D. | pincer-search algorithm. |
| Answer» B. partition algorithm. | |
| 78. |
The biological neuron's _________ is a continuous function rather than a step function. |
| A. | read. |
| B. | write. |
| C. | output. |
| D. | input. |
| Answer» D. input. | |
| 79. |
The _______ step eliminates the extensions of (k-1)-itemsets which are not found to be frequent, frombeing considered for counting support. |
| A. | candidate generation. |
| B. | pruning. |
| C. | partitioning. |
| D. | itemset eliminations. |
| Answer» C. partitioning. | |
| 80. |
If T consist of 500000 transactions, 20000 transaction contain bread, 30000 transaction contain jam,10000 transaction contain both bread and jam. Then the support of bread and jam is _______. |
| A. | 2% |
| B. | 20% |
| C. | 3% |
| D. | 30% |
| Answer» B. 20% | |
| 81. |
The value that says that transactions in D that support X also support Y is called ______________. |
| A. | confidence. |
| B. | support. |
| C. | support count. |
| D. | none of the above. |
| Answer» B. support. | |
| 82. |
Non-additive measures can often combined with additive measures to create new _________.http://grdmcqonline/printqp.php?heading=II M.Sc(IT) [2012-2014], Se...14 of 34 8/20/2013 2:47 PM |
| A. | additive measures. |
| B. | non-additive measures. |
| C. | partially additive. |
| D. | all of the above. |
| Answer» B. non-additive measures. | |
| 83. |
Data mining helps in __________. |
| A. | inventory management. |
| B. | sales promotion strategies. |
| C. | marketing strategies. |
| D. | all of the above. |
| Answer» E. | |
| 84. |
Discovery of cross-sales opportunities is called ________________. |
| A. | segmentation. |
| B. | visualization. |
| C. | correction. |
| D. | association. |
| Answer» E. | |
| 85. |
RBF have only _______________ hidden layer. |
| A. | four. |
| B. | three. |
| C. | two. |
| D. | one. |
| Answer» E. | |
| 86. |
The proportion of transaction supporting X in T is called _________. |
| A. | confidence. |
| B. | support. |
| C. | support count. |
| D. | all of the above. |
| Answer» C. support count. | |
| 87. |
BIRCH is a ________.http://grdmcqonline/printqp.php?heading=II M.Sc(IT) [2012-2014], Se...25 of 34 8/20/2013 2:47 PM |
| A. | agglomerative clustering algorithm. |
| B. | hierarchical algorithm. |
| C. | hierarchical-agglomerative algorithm. |
| D. | divisive. |
| Answer» D. divisive. | |
| 88. |
____________ of data means that the attributes within a given entity are fully dependent on the entireprimary key of the entity. |
| A. | additivity. |
| B. | granularity. |
| C. | functional dependency. |
| D. | dependency. |
| Answer» D. dependency. | |
| 89. |
Black boxes |
| 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» D. None of these | |
| 90. |
Perceptron is |
| A. | General class of approaches to a problem. |
| B. | Performing several computations simultaneously. |
| C. | Structures in a database those are statistically relevant. |
| D. | Simple forerunner of modern neural networks, without hidden layers. |
| Answer» E. | |
| 91. |
A definition or a concept is ———————if it does not classify any examples as coming within the concept |
| A. | Complete |
| B. | Consistent |
| C. | Constant |
| D. | None of these |
| Answer» C. Constant | |
| 92. |
Contingency table is prepared for _______ attribute data. |
| A. | ordinal |
| B. | nominal |
| C. | binay |
| D. | integer |
| Answer» D. integer | |
| 93. |
Multidimensional database is otherwise known as____________. |
| A. | rdbms |
| B. | dbms |
| C. | extended rdbms |
| D. | extended dbms |
| Answer» C. extended rdbms | |
| 94. |
MLP stands for ______________________. |
| A. | mono layer perception. |
| B. | many layer perception. |
| C. | more layer perception. |
| D. | multi layer perception. |
| Answer» E. | |
| 95. |
Patterns that can be discovered from a given database are which type |
| A. | more than one type |
| B. | multiple types always |
| C. | one type only |
| D. | no specific type |
| Answer» B. multiple types always | |
| 96. |
Pick out a k-medoid algoithm. |
| A. | dbscan. |
| B. | birch. |
| C. | pam. |
| D. | cure. |
| Answer» D. cure. | |
| 97. |
Patterns is |
| A. | General class of approaches to a problem. |
| B. | Performing several computations simultaneously. |
| C. | Structures in a database those are statistically relevant |
| D. | Simple forerunner of modern neural networks, without hidden layers. |
| Answer» D. Simple forerunner of modern neural networks, without hidden layers. | |
| 98. |
Overfitting occurs when a model _________. |
| A. | does fit in future states. |
| B. | does not fit in future states. |
| C. | does fit in current state. |
| D. | does not fit in current state. |
| Answer» C. does fit in current state. | |
| 99. |
ROI is an acronym of ________. |
| A. | return on investment. |
| B. | return on information. |
| C. | repetition of information. |
| D. | runtime of instruction |
| Answer» B. return on information. | |
| 100. |
SOMs are used to cluster a specific _____________ dataset containing information about the patient'sdrugs etc. |
| A. | physical. |
| B. | logical. |
| C. | medical. |
| D. | technical. |
| Answer» D. technical. | |