DWDM

101. Online transaction processing , where query is viewed as ---------------transaction.

a) read only b) write only c) read & write d)none of the above [ ]

102. Many people treat data mining as -----------.

a) KDD b) OLTP c) DBMS d) OLAP [ ]

103. --------------- where multiple data sources may be combined.

a) Data selection b) Transformation c) Data mining d) Data integration [ ]

104. Data mining should be applicable to---------------------.

a) Relational database b) data warehouse c)flat files d)all above [ ]

105. A relational data base is a collection of ---------------.

a) tables b) tuples c) attributes d) constraints [ ]

106. ---------------- can be used to generate class labels.

a) clustering b) classification c) prediction d) discrimination [ ]

107. Database size for OLTP is------------------.

a) 100MB to GB b) GB to 10GB c) 10GB to 100GB d) 100 to 1000GB [ ]

108. Number of users of OLAP ----------------

a) ten b) hundred c) thousand d) lakhs [ ]

109. ------------- allows data to be modeled and viewed in multi dimensions.

a) vector b) table c) cube d) none of the above [ ]

110. Data contained in ----------------- tend to be summarized.

a) data mart b) cube c) table d) datawarehouse [ ]

111. In ROLAP ;R stands for-------------.

a) relational b) recurrence c) repository d) rearranged [ ]

112. ----------- special range is used to normalize.

a) [0.0,1.0] b) [1.0,10.00] c) [10.00,100.00] d) [0.0,10.00] [ ]

113. --------- methods smooth a sorted data value by consulting its neighborhood

a) binning b) ignore the tuples c) clustering d) regression [ ]

114. --------- for an attribute A partitions the data distribution of A in to disjoint subsets.

a) histogram b) regression c) clustering d) none of the above [ ]

115.There are ------------ data mining primitives.

a) 5 b) 2 c) 3 d) 4 [ ]

116. ----------- this clause lists the attributes, dimensions for exploration.

a) in relevance to b) from clause c)use database d) having condition [ ]

117. AOI stands for-----------.

a) attribute oriented induction b) alternative online introduction

c) arbitrary online induction d) attribute online induction [ ]

118. --------------- a motivating example for association rule mining .

a) market basket analysis b) student database analysis

c) employee database analysis d) banking system [ ]

119.Association mining has ------------ steps to process.

a)1 b) 2 c) 3 d) 4 [ ]

120. ------------ is the first step used in apriori.

a) join b) prune c)both a& b d) none of the above [ ]

121. Comparing classification methods is done by -------------criteria.

a) speed b) scalability c) robustness d) all the above. [ ]

122. P(H/X) is the --------------- probability.

a) prior b) posterior c) both a & b d) none of the above [ ]

123. -------------which search for frequently occurring patterns in a large data base.

a) association b) back propagation c) bayesian classification d) cross validation [ ]

124. The data mode matrix is called as --------------mode matrix.

a) two b) one c) four d) three [ ]

125. A-------------- variable is generalization of binary variable in that it takes on more than two

states.

a) nominal b) ordinal c) interval d) binary [ ]