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.
| 901. |
NLP stands for____________. |
| A. | Non Language Process |
| B. | Nature Level Program |
| C. | Natural Language Page |
| D. | Natural Language Processing |
| Answer» E. | |
| 902. |
The a priori frequent itemset discovery algorithm moves in the lattice |
| A. | Upward |
| B. | Downward |
| C. | Breadthwise |
| D. | Both upward and downward |
| Answer» B. Downward | |
| 903. |
__________is an example of application development environments. |
| A. | Visual Basic |
| B. | Oracle |
| C. | Sybase |
| D. | SQL Server |
| Answer» B. Oracle | |
| 904. |
The first phase of A Priori algorithm is___________ |
| A. | Candidate generation |
| B. | Itemset generation |
| C. | Pruning |
| D. | Partitioning |
| Answer» B. Itemset generation | |
| 905. |
Pick out a hierarchical clustering algorithm |
| A. | DBSCAN |
| B. | BIRCH |
| C. | PAM |
| D. | CURE |
| Answer» B. BIRCH | |
| 906. |
Which of the following is a data set in the popular UCI machine-learning repository? |
| A. | CLARA. |
| B. | CACTUS. |
| C. | STIRR. |
| D. | MUSHROOM |
| Answer» E. | |
| 907. |
_________is the specialized data warehouse database. |
| A. | Oracle |
| B. | DBZ |
| C. | Informix |
| D. | Redbrick |
| Answer» E. | |
| 908. |
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 | |
| 909. |
is a complex chemical process in neural networks. |
| A. | Receiving process |
| B. | Sending process |
| C. | Transmission process |
| D. | Switching process |
| Answer» D. Switching process | |
| 910. |
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 | |
| 911. |
Query tool is meant for_________. |
| A. | Data acquisition |
| B. | Information delivery |
| C. | Information exchange |
| D. | Communication |
| Answer» B. Information delivery | |
| 912. |
____________ consists of formal definitions, such as a COBOL layout or a database schema. |
| A. | Classical metadata |
| B. | Transformation metadata |
| C. | Historical metadata |
| D. | Structural metadata |
| Answer» B. Transformation metadata | |
| 913. |
____________is the goal of data mining. |
| A. | To explain some observed event or condition |
| B. | To confirm that data exists |
| C. | To analyze data for expected relationships |
| D. | To create a new data warehouse |
| Answer» B. To confirm that data exists | |
| 914. |
The item sets that have completed on full pass move from dashed circle to________ |
| A. | Dashed box |
| B. | Solid circle |
| C. | Solid box |
| D. | None of the above |
| Answer» C. Solid box | |
| 915. |
In web mining, is used to know the order in which URLs tend to be accessed. |
| A. | clustering |
| B. | associations |
| C. | sequential analysis |
| D. | classification |
| Answer» D. classification | |
| 916. |
The time horizon in Data warehouse is usually__________. |
| A. | 1-2 years |
| B. | 3-4years |
| C. | 5-6 years |
| D. | 5-10 years |
| Answer» E. | |
| 917. |
A fact is said to be partially 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» C. Not additive over any dimension | |
| 918. |
Dynamic Itemset Counting Algorithm was proposed by |
| A. | Bin et al |
| B. | Argawal et at |
| C. | Toda et al |
| D. | Simon et at |
| Answer» B. Argawal et at | |
| 919. |
BIRCH is a________ |
| A. | Agglomerative clustering algorithm |
| B. | Hierarchical algorithm |
| C. | Hierarchical-agglomerative algorithm |
| D. | Divisive |
| Answer» D. Divisive | |
| 920. |
Describing some characteristics of a set of data by a general model is viewed as___________. |
| A. | Induction. |
| B. | Compression |
| C. | Approximation |
| D. | Summarization |
| Answer» C. Approximation | |
| 921. |
Extreme values that occur infrequently are called as___________. |
| A. | Outliers |
| B. | Rare values |
| C. | Dimensionality reduction |
| D. | All of the above |
| Answer» B. Rare values | |
| 922. |
Multidimensional database is otherwise known as___________. |
| A. | RDBMS |
| B. | DBMS |
| C. | EXTENDED RDBMS |
| D. | EXTENDED DBMS |
| Answer» C. EXTENDED RDBMS | |
| 923. |
The data is stored, retrieved & updated in___________. |
| A. | OLAP |
| B. | OLTP |
| C. | SMTP |
| D. | FTP |
| Answer» C. SMTP | |
| 924. |
Record cannot be updated in__________. |
| A. | OLTP |
| B. | Files |
| C. | RDBMS |
| D. | data warehouse |
| Answer» E. | |
| 925. |
The technology area associated with CRM is__________. |
| A. | Specialization |
| B. | Generalization |
| C. | Personalization |
| D. | Summarization |
| Answer» D. Summarization | |
| 926. |
Design involves deciding on their centers and the sharpness of their Gaussians. |
| A. | DR |
| B. | AND |
| C. | XOR |
| D. | RBF |
| Answer» E. | |
| 927. |
The output of KDD is ______. |
| A. | Data |
| B. | Information |
| C. | Query |
| D. | Useful information |
| Answer» E. | |
| 928. |
____________is data about data. |
| A. | Metadata |
| B. | Microdata |
| C. | Minidata |
| D. | Multidata |
| Answer» B. Microdata | |
| 929. |
Which of the following is not a data mining metric? |
| A. | Space complexity |
| B. | Time complexity |
| C. | ROI |
| D. | All of the above |
| Answer» E. | |
| 930. |
clustering technique start with as many clusters as there are records, with eachcluster having only one record |
| A. | Agglomerative |
| B. | Divisive |
| C. | Partition |
| D. | Numeric |
| Answer» B. Divisive | |
| 931. |
______ is a the input to KDD. |
| A. | Data |
| B. | Information |
| C. | Query |
| D. | Process |
| Answer» B. Information | |
| 932. |
_____________is an important functional component of the metadata. |
| A. | Digital directory |
| B. | Repository |
| C. | Information directory |
| D. | Data dictionary |
| Answer» D. Data dictionary | |
| 933. |
EIS stands for____________. |
| A. | Extended interface system |
| B. | Executive interface system |
| C. | Executive information system |
| D. | Extendable information system |
| Answer» D. Extendable information system | |
| 934. |
Data that are not of interest to the data mining task is called as _____. |
| A. | Missing data |
| B. | Changing data |
| C. | Irrelevant data |
| D. | Noisy data |
| Answer» D. Noisy data | |
| 935. |
Which of the following is a predictive model? |
| A. | Clustering |
| B. | Regression |
| C. | Summarization |
| D. | Association rules |
| Answer» C. Summarization | |
| 936. |
________ Databases are owned by particular departments or business groups. |
| A. | Informational |
| B. | Operational |
| C. | Both informational and operational |
| D. | Flat |
| Answer» C. Both informational and operational | |
| 937. |
In web mining, is used to find natural groupings of users, pages, etc. |
| A. | Clustering |
| B. | Associations |
| C. | Sequential analysis |
| D. | Classification |
| Answer» B. Associations | |
| 938. |
The ______of data could result in the disclosure of information that is deemed to beconfidential. |
| A. | Authorized use |
| B. | Unauthorized use |
| C. | Authenticated use |
| D. | Unauthenticated use |
| Answer» C. Authenticated use | |
| 939. |
The granularity of the fact is the ___________ of detail at which it is recorded. |
| A. | Transformation |
| B. | Summarization |
| C. | Level |
| D. | Tr |
| Answer» B. Summarization | |
| 940. |
The goal of________is to discover both the dense and sparse regions of a data set |
| A. | Association rule |
| B. | Classification |
| C. | Clustering |
| D. | Genetic Algorithm |
| Answer» D. Genetic Algorithm | |
| 941. |
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% | |
| 942. |
Which of the following is not a desirable feature of any efficient algorithm? |
| A. | To reduce number of input operation |
| B. | To reduce number of output operations |
| C. | To be efficient in computing |
| D. | To have maximal code length |
| Answer» E. | |
| 943. |
The star schema is composed of __________ fact table. |
| A. | one |
| B. | Two |
| C. | Three |
| D. | four |
| Answer» B. Two | |
| 944. |
________is a process of determining the preference of customer's majority. |
| A. | Association |
| B. | Preferencing |
| C. | Segmentation |
| D. | Classification |
| Answer» C. Segmentation | |
| 945. |
Employs the supervised mode of learning. |
| A. | RBF |
| B. | MLP |
| C. | MLP & RBF |
| D. | ANN |
| Answer» D. ANN | |
| 946. |
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. | |
| 947. |
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 | |
| 948. |
__________maps the core warehouse metadata to business concepts, familiar and useful toend users. |
| A. | Application level metadata |
| B. | User level metadata |
| C. | Enduser level metadata |
| D. | Core level metadata |
| Answer» B. User level metadata | |
| 949. |
Investment analysis used in neural networks is to predict the movement of_________fromprevious data. |
| A. | Engines |
| B. | Stock |
| C. | Patterns |
| D. | Models |
| Answer» C. Patterns | |
| 950. |
A priori algorithm is otherwise called as_________ |
| A. | Width-wise algorithm |
| B. | Level-wise algorithm |
| C. | Pincer-search algorithm |
| D. | FP growth algorithm |
| Answer» C. Pincer-search algorithm | |