Top 350+ Solved Data Mining and Data Warehouse MCQ Questions Answer
Q. Noise is
a. A component of a network
b. In the context of KDD and data mining, this refers to random errors in a database table.
c. One of the defining aspects of a data warehouse
d. None of these
Q. Quadratic complexity is
a. A reference to the speed of an algorithm, which is quadratically dependent on the size of the dat(A)
b. Attributes of a database table that can take only numerical values.
c. Tools designed to query a database.
d. None of these
Q. Query tools are
a. A reference to the speed of an algorithm, which is quadratically dependent on the size of the dat(A)
b. Attributes of a database table that can take only numerical values.
c. Tools designed to query a database.
d. None of these
Q. Prolog is
a. A programming language based on logic
b. A computer where each processor has its own operating system, its own memory, and its own hard disk.
c. Describes the structure of the contents of a database.
d. None of these
Q. Massively parallel machine is
a. A programming language based on logic
b. A computer where each processor has its own operating system, its own memory, and its own hard disk
c. Describes the structure of the contents of a database.
d. None of these
Q. Meta-data is
a. A programming language based on logic
b. A computer where each processor has its own operating system, its own memory, and its own hard disk.
c. Describes the structure of the contents of a database
d. None of these
Q. n(log n) is referred to
a. A measure of the desired maximal complexity of data mining algorithms
b. A database containing volatile data used for the daily operation of an organization
c. Relational database management system
d. None of these
Q. Operational database is
a. A measure of the desired maximal complexity of data mining algorithms
b. A database containing volatile data used for the daily operation of an organization
c. Relational database management system
d. None of these
Q. Oracle is referred to
a. A measure of the desired maximal complexity of data mining algorithms
b. A database containing volatile data used for the daily operation of an organization
c. Relational database management system
d. None of these
Q. Paradigm 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.
Q. 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.
Q. Parallelism 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.
Q. 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.
Q. Shallow knowledge
a. The large set of candidate solutions possible for a problem
b. The information stored in a database that can be, retrieved with a single query.
c. Worth of the output of a machine- learning program that makes it under- standable for humans
d. None of these
Q. 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