Quiz  /  Data Mining MCQ Questions and Answers

  • 1. 
    Classification is

  • A subdivision of a set of examples into a number of classes
  • A measure of the accuracy, of the classification of a concept that is given by a certain theory
  • The task of assigning a classification to a set of examples
  • None of these

  • 2. 
    Some telecommunication company wants to segment their customers into distinct groups in order to send appropriate subscription offers, this is an example of

  • Supervised learning
  • Data extraction
  • Serration
  • Unsupervised learning

  • 3. 
    Self-organizing maps are an example of

  • Unsupervised learning
  • Supervised learning
  • Reinforcement learning
  • Missing data imputation

  • 4. 
    You are given data about seismic activity in Japan, and you want to predict a magnitude of the next earthquake, this is in an example of

  • Supervised learning
  • Unsupervised learning
  • Serration
  • Dimensionality reduction

  • 5. 
    Assume you want to perform supervised learning and to predict number of newborns according to size of storks’ population (http://www.brixtonhealth.com/storksBabies.pdf), it is an example of

  • Classification
  • Regression
  • Clustering
  • Structural equation modeling

  • 6. 
    In the example of predicting number of babies based on storks’ population size, number of babies is

  • outcome
  • feature
  • attribute
  • observation

  • 7. 
    which of the following is not involve in data mining?

  • Knowledge extraction
  • Data archaeology
  • Data exploration
  • Data transformation

  • 8. 
    Which of the following issue is considered before investing in Data Mining?

  • Functionality
  • Vendor consideration
  • Compatibility
  • All of the above

  • 9. 
    Adaptive system management is

  • It uses machine-learning techniques. Here program can learn from past experience and adapt themselves to new situations
  • Computational procedure that takes some value as input and produces some value as output.
  • Science of making machines performs tasks that would require intelligence when performed by humans
  • none of these

  • 10. 
    Bayesian classifiers is

  • A class of learning algorithm that tries to find an optimum classification of a set of examples using the probabilistic theory.
  • Any mechanism employed by a learning system to constrain the search space of a hypothesis
  • 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.
  • None of these

  • 11. 
    Algorithm is

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

  • 12. 
    Bias is

  • class of learning algorithm that tries to find an optimum classification of a set of examples using the probabilistic theory
  • Any mechanism employed by a learning system to constrain the search space of a hypothesis
  • 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.
  • None of these

  • 13. 
    Background knowledge referred to

  • Additional acquaintance used by a learning algorithm to facilitate the learning process
  • A neural network that makes use of a hidden layer
  • It is a form of automatic learning.
  • None of these

  • 14. 
    Case-based learning is

  • A class of learning algorithm that tries to find an optimum classification of a set of examples using the probabilistic theory.
  • Any mechanism employed by a learning system to constrain the search space of a hypothesis
  • 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.
  • None of these

  • 15. 
    Binary attribute are

  • This takes only two values. In general, these values will be 0 and 1 and .they can be coded as one bit
  • The natural environment of a certain species
  • Systems that can be used without knowledge of internal operations
  • None of these

  • 16. 
    Classification accuracy is

  • A subdivision of a set of examples into a number of classes
  • Measure of the accuracy, of the classification of a concept that is given by a certain theory
  • The task of assigning a classification to a set of examples
  • None of these

  • 17. 
    Biotope are and they can be coded as one bit.

  • This takes only two values. In general, these values will be 0 and 1
  • The natural environment of a certain species
  • Systems that can be used without knowledge of internal operations
  • None of these

  • 18. 
    Cluster is

  • Group of similar objects that differ significantly from other objects
  • Operations on a database to transform or simplify data in order to prepare it for a machine-learning algorithm
  • Symbolic representation of facts or ideas from which information can potentially be extracted
  • None of these

  • 19. 
    Black boxes are and they can be coded as one bit.

  • This takes only two values. In general, these values will be 0 and 1
  • The natural environment of a certain species
  • Systems that can be used without knowledge of internal operations
  • None of these

  • 20. 
    A definition of a concept is if it recognizes all the instances of that concept

  • Complete
  • Consistent
  • Constant
  • None of these

  • 21. 
    Data mining is

  • The actual discovery phase of a knowledge discovery process
  • The stage of selecting the right data for a KDD process
  • A subject-oriented integrated time variant non-volatile collection of data in support of management
  • None of these

  • 22. 
    A definition or a concept is if it classifies any examples as coming within the concept

  • Complete
  • Consistent
  • Constant
  • None of these

  • 23. 
    Data independence means

  • Data is defined separately and not included in programs
  • Programs are not dependent on the physical attributes of data.
  • Programs are not dependent on the logical attributes of data
  • Both (B) and (C).

  • 24. 
    E-R model uses this symbol to represent weak entity set?

  • Dotted rectangle
  • Diamond
  • Doubly outlined rectangle
  • None of these

  • 25. 
    SET concept is used in

  • Network Model
  • Hierarchical Model
  • Relational Model
  • None of these

  • 26. 
    Relational Algebra is

  • Data Definition Language
  • Meta Language
  • Procedural query Language
  • None of the above

  • 27. 
    Key to represent relationship between tables is called

  • Primary key
  • Secondary Key
  • Foreign Key
  • None of these

  • 28. 
    ________ produces the relation that has attributes of Ri and R2

  • Cartesian product
  • Difference
  • Intersection
  • Product

  • 29. 
    Which of the following are the properties of entities?

  • Groups
  • Table
  • Attributes
  • Switchboards

  • 30. 
    In a relation

  • Ordering of rows is immaterial
  • No two rows are identical
  • (A) and (B) both are true
  • None of these
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