Data Mining, Data Warehouse MCQ, Chapter-01

Posted by

DATA MINING AND DATA WAREHOUSE

1. Adaptive system management is
(A) It uses machine-learning techniques. Here program can learn from past experience and adapt themselves to new situations
(B) Computational procedure that takes some value as input and produces some value as output.
(C) Science of making machines performs tasks that would require intelligence when performed by humans
(D) None of these

2. Algorithm is
(A) It uses machine-learning techniques. Here program can learn from past experience and adapt themselves to new situations
(B) Computational procedure that takes some value as input and produces some value as output
(C) Science of making machines performs tasks that would require intelligence when performed by humans
(D) None of these

3. Background knowledge referred to
(A) Additional acquaintance used by a learning algorithm to facilitate the learning process
(B) A neural network that makes use of a hidden layer.
(C) It is a form of automatic learning.
(D) None of these

4. Back propagation networks is
(A) Additional acquaintance used by a learning algorithm to facilitate the learning process
(B) A neural network that makes use of a hidden layer
(C) It is a form of automatic learning.
(D) None of these

5. Bayesian classifiers is
(A) A class of learning algorithm that tries to find an optimum classification of a set of examples using the probabilistic theory.
(B) Any mechanism employed by a learning system to constrain the search space of a hypothesis.
(C) An approach to the design of learning algorithms that is inspired by the fact that when people encounter new situations, they often explain them by reference to familiar experiences, adapting the explanations to fit the new situation.
(D) None of these

6. Bias is
(A) A class of learning algorithm that tries to find an optimum classification of a set of examples using the probabilistic theory.
(B) Any mechanism employed by a learning system to constrain the search space of a hypothesis.
(C) An approach to the design of learning algorithms that is inspired by the fact that when people encounter new situations, they often explain them by reference to familiar experiences, adapting the explanations to fit the new situation.
(D) None of these

7. Case-based learning is
(A) A class of learning algorithm that tries to find an optimum classification of a set of examples using the probabilistic theory.
(B) Any mechanism employed by a learning system to constrain the search space of a hypothesis.
(C) An approach to the design of learning algorithms that is inspired by the fact that when people encounter new situations, they often explain them by reference to familiar experiences, adapting the explanations to fit the new situation.
(D) None of these

8. Binary attribute are
(A) This takes only two values. In general, these values will be 0 and 1 and they can be coded as one bit
(B) The natural environment of a certain species
(C) Systems that can be used without knowledge of internal operations
(D) None of these

9. Biotope are
(A) This takes only two values. In general, these values will be 0 and 1 and they can be coded as one bit.
(B) The natural environment of a certain species
(C) Systems that can be used without knowledge of internal operations
(D) None of these

10. Black boxes
(A) This takes only two values. In general, these values will be 0 and 1 and they can be coded as one bit.
(B) The natural environment of a certain species
(C) Systems that can be used without knowledge of internal operations
(D) None of these

11. Artificial intelligence is
(A) It uses machine-learning techniques. Here program can learn from past experience and adapt themselves to new situations
(B) Computational procedure that takes some value as input and produces some value as output.
(C) Science of making machines performs tasks that would require intelligence when performed by humans
(D) None of these

12. Cache is
(A) It is a memory buffer that is used to store data that is needed frequently by an algorithm in order to minimize input/ output traffic
(B) The number of different values that a given attribute can take
(C) A mathematical conception of space where the location of a point is given by reference to its distance from two or three axes intersecting at right angles
(D) None of these

13. Cardinality of an attribute is
(A) It is a memory buffer that is used to store data that is needed frequently by an algorithm in order to minimize input/ output traffic
(B) The number of different values that a given attribute can take
(C) A mathematical conception of space where the location of a point is given by reference to its distance from two or three axes intersecting at right angles
(D) None of these

14. Cartesian space is
(A) It is a memory buffer that is used to store data that is needed frequently by an algorithm in order to minimize input/ output traffic
(B) The number of different values that a given attribute can take
(C) A mathematical conception of space where the location of a point is given by reference to its distance from two or three axes intersecting at right angles
(D) None of these

15. Classification is
(A) A subdivision of a set of examples into a number of classes
(B) A measure of the accuracy, of the classification of a concept that is given by a certain theory
(C) The task of assigning a classification to a set of examples
(D) None of these

16. Classification accuracy is
(A) A subdivision of a set of examples into a number of classes
(B) Measure of the accuracy, of the classification of a concept that is given by a certain theory
(C) The task of assigning a classification to a set of examples
(D) None of these

17. Cluster is
(A) Group of similar objects that differ significantly from other objects
(B) Operations on a database to transform or simplify data in order to prepare it for a machine-learning algorithm
(C) Symbolic representation of facts or ideas from which information can potentially be extracted
(D) None of these

18. Data is
(A) Group of similar objects that differ significantly from other objects
(B) Operations on a database to transform or simplify data in order to prepare it for a machine-learning algorithm
(C) Symbolic representation of facts or ideas from which information can potentially be extracte(D)
(D) None of these

19. A definition of a concept is——if it recognizes all the instances of that concept.
(A) Complete
(B) Consistent
(C) Constant
(D) None of these

20. A definition or a concept is ———————if it does not classify any examples as coming within the concept
(A) Complete
(B) Consistent
(C) Constant
(D) None of these


Answer Sheet
1. (A) 2. (B) 3. (A) 4. (B) 5. (A)
6. (B) 7. (C) 8. (A) 9. (B) 10. (C)
11. (C) 12. (A) 13. (B) 14. (A) 15. (A)
16. (B) 17. (A) 18. (C) 19. (A) 20. (B)