Explore topic-wise MCQs in Computer Science Engineering (CSE).

This section includes 45 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.

1.

Bill Inmon has estimated___________of the time required to build a data warehouse, is consumed in the conversion process.

A. 10 percent.
B. 20 percent.
C. 40 percent
D. 80 percent.
Answer» E.
2.

____________ 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.
3.

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.
4.

Certain itemsets in the dashed circle whose support count reach support value during an iteration move into the ______.

A. dashed box.
B. solid circle.
C. solid box.
D. none of the above.
Answer» B. solid circle.
5.

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.
6.

____________ contains information that gives users an easy-to-understand perspective of the information stored in the data warehouse.

A. business metadata.
B. technical metadata.
C. operational metadata.
D. financial metadata.
Answer» B. technical metadata.
7.

___________ of data means that the attributes within a given entity are fully dependent on the entire primary key of the entity.

A. additivity.
B. granularity.
C. functional dependency.
D. dimensionality.
Answer» D. dimensionality.
8.

The ____________ of data could result in the disclosure of information that is deemed to be confidential.

A. authorized use.
B. unauthorized use.
C. authenticated use.
D. unauthenticated use.
Answer» C. authenticated use.
9.

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%
10.

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.
11.

____________ of data means that the attributes within a given entity are fully dependent on the entire primary key of the entity.

A. additivity.
B. granularity.
C. functional dependency.
D. dependency.
Answer» D. dependency.
12.

All set of items whose support is greater than the user-specified minimum support are called as _____________.

A. border set.
B. frequent set.
C. maximal frequent set.
D. lattice.
Answer» C. maximal frequent set.
13.

SOMs are used to cluster a specific _____________ dataset containing information about the patient's drugs etc.

A. physical.
B. logical.
C. medical.
D. technical.
Answer» D. technical.
14.

The ________ algorithm is based on the observation that the frequent sets are normally very few in number compared to the set of all itemsets.

A. a priori.
B. clustering.
C. association rule.
D. partition.
Answer» E.
15.

The ________ algorithm is based on the observation that the frequent sets are normally very few in number compared to the set of all itemsets.

A. a priori.
B. clustering.
C. association rule.
D. partition.
Answer» E.
16.

SOMs are used to cluster a specific _____________ dataset containing information about the patient's drugs etc.

A. physical.
B. logical.
C. medical.
D. technical.
Answer» D. technical.
17.

__________ clustering techniques starts with all records in one cluster and then try to split that cluster into small pieces.

A. agglomerative.
B. divisive.
C. partition.
D. numeric.
Answer» C. partition.
18.

__________ clustering techniques starts with all records in one cluster and then try to split that cluster into small pieces.

A. agglomerative.
B. divisive.
C. partition.
D. numeric.
Answer» C. partition.
19.

The important aspect of the data warehouse environment is that data found within the data warehouse is___________.

A. subject-oriented.
B. time-variant.
C. integrated.
D. all of the above.
Answer» E.
20.

Effect of one attribute value on a given class is independent of values of other attribute is called _________.

A. value independence.
B. class conditional independence.
C. conditional independence.
D. unconditional independence.
Answer» B. class conditional independence.
21.

An algorithm called________is used to generate the candidate item sets for each pass after the first.

A. apriori.
B. apriori-gen.
C. sampling.
D. partition.
Answer» C. sampling.
22.

________ displays of data such as maps, charts and other graphical representation allow data to be presented compactly to the users.

A. hidden
B. visual
C. obscured
D. concealed
Answer» C. obscured
23.

In a feed- forward networks, the conncetions between layers are ___________ from input to output.

A. bidirectional.
B. unidirectional.
C. multidirectional.
D. directional.
Answer» C. multidirectional.
24.

___________ training may be used when a clear link between input data sets and target output values does not exist.

A. competitive.
B. perception.
C. supervised.
D. unsupervised.
Answer» E.
25.

___________ training may be used when a clear link between input data sets and target output values does not exist.

A. competitive.
B. perception.
C. supervised.
D. unsupervised.
Answer» E.
26.

__________ is a subject-oriented, integrated, time-variant, nonvolatile collection of data in support of management decisions.

A. data mining.
B. data warehousing.
C. web mining.
D. text mining.
Answer» C. web mining.
27.

The transformed prefix paths of a node 'a' form a truncated database of pattern which co-occur with a is called _______.

A. suffix path.
B. fp-tree.
C. conditional pattern base.
D. prefix path.
Answer» D. prefix path.
28.

___________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.
29.

In ___________ each cluster is represented by one of the objects of the cluster located near the center.

A. k-medoid.
B. k-means.
C. stirr.
D. rock.
Answer» B. k-means.
30.

________is the most well known association rule algorithm and is used in most commercial products.

A. apriori algorithm.
B. partition algorithm.
C. distributed algorithm.
D. pincer-search algorithm.
Answer» B. partition algorithm.
31.

__________ 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» D. data repository.
32.

_______ clustering technique start with as many clusters as there are records, with each cluster having only one record.

A. agglomerative.
B. divisive.
C. partition.
D. numeric.
Answer» B. divisive.
33.

Investment analysis used in neural networks is to predict the movement of _________ from previous data.

A. engines.
B. stock.
C. patterns.
D. models.
Answer» C. patterns.
34.

Investment analysis used in neural networks is to predict the movement of _________ from previous data.

A. engines.
B. stock.
C. patterns.
D. models.
Answer» C. patterns.
35.

_________maps the core warehouse metadata to business concepts, familiar and useful to end users.

A. application level metadata.
B. user level metadata.
C. enduser level metadata.
D. core level metadata.
Answer» B. user level metadata.
36.

The basic partition algorithm reduces the number of database scans to ________ & divides it into partitions.

A. one.
B. two.
C. three.
D. four.
Answer» C. three.
37.

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.
38.

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.
39.

RBF hidden layer units have a receptive field which has a ____________; that is, a particular input value at which they have a maximal output.

A. top.
B. bottom.
C. centre.
D. border.
Answer» D. border.
40.

7 If T consist of 500000 transactions, 20000 transaction contain bread, 30000 transaction containjam, 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.
41.

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.
42.

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%
43.

___________ of data means that the attributes within a given entity are fully dependent on the entire primary key of the entity.

A. additivity.
B. granularity.
C. functional dependency.
D. dimensionality.
Answer» D. dimensionality.
44.

____________ of data means that the attributes within a given entity are fully dependent on the entire primary key of the entity.

A. additivity.
B. granularity.
C. functional dependency.
D. dependency.
Answer» D. dependency.
45.

The transformed prefix paths of a node 'a' form a truncated database of pattern which co-occur with a is called _______.

A. suffix path.
B. fp-tree.
C. conditional pattern base.
D. prefix path.
Answer» D. prefix path.