MCQOPTIONS
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MCQOPTIONS
This section includes 3246 Mcqs, each offering curated multiple-choice questions to sharpen your Current Affairs knowledge and support exam preparation. Choose a topic below to get started.
| 1051. |
_________is held in the catalog of the warehouse database system. |
| A. | Application level metadata |
| B. | Algorithmic level metadata |
| C. | Departmental level metadata |
| D. | Core warehouse metadata |
| Answer» C. Departmental level metadata | |
| 1052. |
The basic partition algorithm reduces the number of database scans to __________ & dividesit into partitions |
| A. | One |
| B. | Two |
| C. | Three |
| D. | Four |
| Answer» C. Three | |
| 1053. |
The basic idea of the Apriori algorithm is to generate_____item sets of a particular size &scans the database |
| A. | Candidate |
| B. | Primary |
| C. | Secondary |
| D. | Superkey |
| Answer» B. Primary | |
| 1054. |
The generic two-level data warehouse architecture includes________. |
| A. | At least one data mart |
| B. | Data that can extracted from numerous internal and external sources |
| C. | Near real-time updates |
| D. | Far real-time updates |
| Answer» D. Far real-time updates | |
| 1055. |
The extract process is __________. |
| A. | Capturing all of the data contained in various operational systems |
| B. | Capturing a subset of the data contained in various operational systems |
| C. | Capturing all of the data contained in various decision support systems |
| D. | Capturing a subset of the data contained in various decision supportsystems |
| Answer» C. Capturing all of the data contained in various decision support systems | |
| 1056. |
In a feed- forward networks, the connections between layers are________from input tooutput. |
| A. | Bidirectional |
| B. | Unidirectional |
| C. | Multidirectional |
| D. | Directional |
| Answer» C. Multidirectional | |
| 1057. |
Is the connectivity of the neuron that give simple devices their real power? |
| A. | Water |
| B. | Air |
| C. | Power |
| D. | Fire |
| Answer» E. | |
| 1058. |
Pick out a k-medoid algorithm |
| A. | DBSCAN |
| B. | BIRCH |
| C. | PAM |
| D. | CURE |
| Answer» D. CURE | |
| 1059. |
Incorrect or invalid data is known as _______. |
| A. | Changing data |
| B. | Noisy data |
| C. | Outliers |
| D. | Missing data |
| Answer» C. Outliers | |
| 1060. |
________of data means that the attributes within a given entity are fully dependent on theentire primary key of the entity. |
| A. | Additively |
| B. | Granularity |
| C. | Functional dependency |
| D. | Dimensionality |
| Answer» D. Dimensionality | |
| 1061. |
Reducing the number of attributes to solve the high dimensionality problem is calledas_____________. |
| A. | Dimensionality curse |
| B. | Dimensionality reduction |
| C. | Cleaning |
| D. | Over fitting |
| Answer» C. Cleaning | |
| 1062. |
Highly summarized data is __________. |
| A. | Compact and easily accessible |
| B. | Compact and expensive |
| C. | Compact and hardly accessible |
| D. | Compact |
| Answer» B. Compact and expensive | |
| 1063. |
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» B. Older detail data | |
| 1064. |
The_______algorithm is based on the observation that the frequent sets are normally veryfew in number compared to the set of all itemsets |
| A. | A priori |
| B. | Clustering |
| C. | Association rule |
| D. | Partition |
| Answer» E. | |
| 1065. |
Itemsets in the category of structures have a counter and the stop number with them |
| A. | Dashed |
| B. | Circle |
| C. | Box |
| D. | Solid |
| Answer» B. Circle | |
| 1066. |
The data Warehouse is __________. |
| A. | Read only |
| B. | Write only |
| C. | Read write only |
| D. | None |
| Answer» B. Write only | |
| 1067. |
Box plot and scatter diagram techniques are_________. |
| A. | Graphical |
| B. | Geometri |
| C. | C Icon-base |
| D. | D Pixel-based |
| Answer» C. C Icon-base | |
| 1068. |
Any superset of an infrequent set is an infrequent set. This is ___________ |
| A. | Maximal frequent set |
| B. | Border set |
| C. | Upward closure property |
| D. | Downward closure property |
| Answer» D. Downward closure property | |
| 1069. |
Data can be updated in ______ environment. |
| A. | Data warehouse |
| B. | Data mining |
| C. | Operational |
| D. | Informational |
| Answer» D. Informational | |
| 1070. |
Discovery of cross-sales opportunities is called _________. |
| A. | Segmentation |
| B. | Visualization |
| C. | Correction |
| D. | Association |
| Answer» E. | |
| 1071. |
A fact is said to be non-additive if_______. |
| A. | It is additive over every dimension of its dimensionality |
| B. | Additive over at least one but not all of the dimensions |
| C. | Not additive over any dimension |
| D. | None of the above |
| Answer» D. None of the above | |
| 1072. |
Certain itemsets enter afresh into the system and get into the , which are essentially the supersets of the itemsets that move from the dashed circle to the dashed box |
| A. | Dashed box |
| B. | Solid circle |
| C. | Solid box |
| D. | Dashed circle |
| Answer» E. | |
| 1073. |
Treating incorrect or missing data is called as________. |
| A. | Selection |
| B. | Preprocessing |
| C. | Transformation |
| D. | Interpretation |
| Answer» C. Transformation | |
| 1074. |
The dimension tables describe the __________. |
| A. | Entities |
| B. | Facts |
| C. | Keys |
| D. | Units of measures |
| Answer» C. Keys | |
| 1075. |
The frequent-item-header-table consists of fields |
| A. | Only one. |
| B. | Two. |
| C. | Three. |
| D. | Four |
| Answer» C. Three. | |
| 1076. |
Granularity is determined by___________. |
| A. | Number of parts to a key |
| B. | Granularity of those parts |
| C. | Both A and B |
| D. | None of the above |
| Answer» D. None of the above | |
| 1077. |
RBF stands for . |
| A. | Radial basis function |
| B. | Radial bio function |
| C. | Radial big function |
| D. | Radial bi function |
| Answer» B. Radial bio function | |
| 1078. |
___________is a data transformation process. |
| A. | Comparison |
| B. | Projection |
| C. | Selection |
| D. | Filtering |
| Answer» E. | |
| 1079. |
Dimensionality reduction reduces the data set size by removing_____________. |
| A. | Relevant attributes |
| B. | Irrelevant attributes |
| C. | Derived attributes |
| D. | Composite attributes |
| Answer» C. Derived attributes | |
| 1080. |
____________is data collected from natural systems. |
| A. | MRI scan |
| B. | ODS data |
| C. | Statistical data |
| D. | Historical data |
| Answer» B. ODS data | |
| 1081. |
7 If T consist of 500000 transactions, 20000 transaction contain bread, 30000 transaction contain jam, 10000 transaction contain both bread and jam. Then the confidence of buying bread with jam is____________. |
| A. | 33.33% |
| B. | 66.66% |
| C. | 45% |
| D. | 50% |
| Answer» E. | |
| 1082. |
Source data from the warehouse comes from__________. |
| A. | ODS |
| B. | TDS |
| C. | MDDB |
| D. | ORDBMS |
| Answer» B. TDS | |
| 1083. |
The full form of KDD is__________. |
| A. | Knowledge database |
| B. | Knowledge discovery in database |
| C. | Knowledge data house |
| D. | Knowledge data definition |
| Answer» C. Knowledge data house | |
| 1084. |
The modern CASE tools belong to_________category. |
| A. | Analysis |
| B. | Development |
| C. | Coding |
| D. | Delivery |
| Answer» B. Development | |
| 1085. |
______ helps to uncover hidden information about the data. |
| A. | Induction |
| B. | Compression |
| C. | Approximation |
| D. | Summarization |
| Answer» D. Summarization | |
| 1086. |
Prediction can be viewed as forecasting a value |
| A. | Non-continuous. |
| B. | Constant. |
| C. | Continuous. |
| D. | variable |
| Answer» D. variable | |
| 1087. |
Mining is concerned with discovering the model underlying the link structures of theweb. |
| A. | Data structure |
| B. | Web structure |
| C. | Text structure |
| D. | Image structure |
| Answer» C. Text structure | |
| 1088. |
The power of self-learning system lies in___________. |
| A. | Cost |
| B. | Speed |
| C. | Accuracy |
| D. | Simplicity |
| Answer» D. Simplicity | |
| 1089. |
___________is a method of incremental conceptual clustering. |
| A. | CORBA |
| B. | OLAP |
| C. | COBWEB |
| D. | STING |
| Answer» D. STING | |
| 1090. |
The itemsets in the_________category structures are not subjected to any counting |
| A. | Dashes |
| B. | Box |
| C. | Soli |
| D. | D Circle |
| Answer» D. D Circle | |
| 1091. |
is concerned with discovering the model underlying the link structures of the web. |
| A. | Web content mining. |
| B. | Web structure mining. |
| C. | Web usage mining. |
| D. | All of the above |
| Answer» C. Web usage mining. | |
| 1092. |
Data mining helps in________. |
| A. | Inventory managemen |
| B. | Sales promotion strategies |
| C. | Marketing strategies |
| D. | All of the above |
| Answer» E. | |
| 1093. |
A frequent pattern tree is a tree structure consisting of ________ |
| A. | An item-prefix-tree |
| B. | A frequent-item-header table |
| C. | A frequent-item-node |
| D. | Both A & B |
| Answer» E. | |
| 1094. |
The__________is a long, single fiber that originates from the cell body. |
| A. | Axon |
| B. | Neuron |
| C. | Dendrites |
| D. | Strands |
| Answer» B. Neuron | |
| 1095. |
Expansion for DSS in DW is _________. |
| A. | Decision Support system |
| B. | Decision Single System |
| C. | Data Storable System |
| D. | Data Support System |
| Answer» B. Decision Single System | |
| 1096. |
Which of the following is not a primary grain in analytical modeling. |
| A. | Transaction |
| B. | Periodic snapshot |
| C. | Accumulating snapshot |
| D. | All of the above |
| Answer» C. Accumulating snapshot | |
| 1097. |
___________defines the structure of the data held in operational databases and used byoperational applications. |
| A. | User-level metadata |
| B. | Data warehouse metadata |
| C. | Operational metadata |
| D. | Data mining metadata |
| Answer» D. Data mining metadata | |
| 1098. |
______ maps data into predefined groups. |
| A. | Regression |
| B. | Time series analysis |
| C. | Prediction |
| D. | Classification |
| Answer» E. | |
| 1099. |
The problem of dimensionality curse involves___________. |
| A. | The use of some attributes may interfere with the correct completion of a data mining task. |
| B. | The use of some attributes may simply increase the overall complexity. |
| C. | Some may decrease the efficiency of the algorithm. |
| D. | All of the above |
| Answer» E. | |
| 1100. |
Removing duplicate records is a process called____________. |
| A. | Recovery |
| B. | Data cleaning |
| C. | Data cleansing |
| D. | Data pruning |
| Answer» C. Data cleansing | |