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This set of Data Mining and Data Warehouse Multiple Choice Questions & Answers (MCQs) focuses on Data Mining And Warehouse Set 15

Q1 | Expert systems
  • Combining different types of method or information
  • Approach to the design of learning algorithms that is structured along the lines of the theory of evolution.
  • Decision support systems that contain an Information base filled with the knowledge of an expert formulated in terms of if-then rules
  • None of these
Q2 | Extendible architecture is
  • Modular design of a software application that facilitates the integration of new modules
  • Showing a universal law or rule to be invalid by providing a counter example
  • A set of attributes in a database table that refers to data in another table
  • None of these
Q3 | Falsification is
  • Modular design of a software application that facilitates the integration of new modules
  • Showing a universal law or rule to be invalid by providing a counter example
  • A set of attributes in a database table that refers to data in another table
  • None of these
Q4 | Foreign key is
  • Modular design of a software application that facilitates the integration of new modules
  • Showing a universal law or rule to be invalid by providing a counter example
  • A set of attributes in a database table that refers to data in another table
  • None of these
Q5 | Hybrid learning is
  • Machine-learning involving different techniques
  • The learning algorithmic analyzes the examples on a systematic basis and makes incremental adjustments to the theory that is learned
  • Learning by generalizing from examples
  • None of these
Q6 | Incremental learning referred to
  • Machine-learning involving different techniques
  • The learning algorithmic analyzes the examples on a systematic basis and makes incremental adjustments to the theory that is learned
  • Learning by generalizing from examples
  • None of these
Q7 | Information content is
  • The amount of information with in data as opposed to the amount of redundancy or noise
  • One of the defining aspects of a data warehouse
  • Restriction that requires data in one column of a database table to the a sub- set of another-column.
  • None of these
Q8 | Inclusion dependencies
  • The amount of information with in data as opposed to the amount of redundancy or noise
  • One of the defining aspects of a data warehouse
  • Restriction that requires data in one column of a database table to the a sub- set of another-column
  • None of these
Q9 | KDD (Knowledge Discovery in Databases) is referred to
  • Non-trivial extraction of implicit previously unknown and potentially useful information from dat(A)
  • Set of columns in a database table that can be used to identify each record within this table uniquely.
  • collection of interesting and useful patterns in a database
  • none of these
Q10 | Key is referred to
  • Non-trivial extraction of implicit previously unknown and potentially useful information from dat(A)
  • Set of columns in a database table that can be used to identify each record within this table uniquely
  • collection of interesting and useful patterns in a database
  • none of these
Q11 | Inductive learning is
  • Machine-learning involving different techniques
  • The learning algorithmic analyzes the examples on a systematic basis and makes incremental adjustments to the theory that is learned
  • Learning by generalizing from examples
  • None of these
Q12 | Integrated is
  • The amount of information with in data as opposed to the amount of redundancy or noise
  • One of the defining aspects of a data warehouse
  • Restriction that requires data in one column of a database table to the a sub- set of another-column.
  • None of these
Q13 | Knowledge engineering is
  • The process of finding the right formal representation of a certain body of knowledge in order to represent it in a knowledge-based system
  • It automatically maps an external signal space into a system’s internal representational space. They are useful in the performance of classification tasks.
  • A process where an individual learns how to carry out a certain task when making a transition from a situation in which the task cannot be carried out to a situation in which the same task under the same circumstances can be carried out.
  • None of these
Q14 | Kohonen self-organizing map referred to
  • The process of finding the right formal representation of a certain body of knowledge in order to represent it in a knowledge-based system
  • It automatically maps an external signal space into a system’s internal representational space. They are useful in the performance of classification tasks
  • A process where an individual learns how to carry out a certain task when making a transition from a situation in which the task cannot be carried out to a situation in which the same task under the same circumstances can be carried out.
  • None of these
Q15 | Learning is
  • The process of finding the right formal representation of a certain body of knowledge in order to represent it in a knowledge-based system
  • It automatically maps an external signal space into a system’s internal representational space. They are useful in the performance of classification tasks.
  • A process where an individual learns how to carry out a certain task when making a transition from a situation in which the task cannot be carried out to a situation in which the same task under the same circumstances can be carried out.
  • None of these
Q16 | Learning algorithm referrers to
  • An algorithm that can learn
  • A sub-discipline of computer science that deals with the design and implementation of learning algorithms.
  • A machine-learning approach that abstracts from the actual strategy of an individual algorithm and can therefore be applied to any other form of machine learning.
  • None of these
Q17 | Meta-learning is
  • An algorithm that can learn
  • A sub-discipline of computer science that deals with the design and implementation of learning algorithms.
  • A machine-learning approach that abstracts from the actual strategy of an individual algorithm and can therefore be applied to any other form of machine learning.
  • None of these
Q18 | Machine learning is
  • An algorithm that can learn
  • A sub-discipline of computer science that deals with the design and implementation of learning algorithms.
  • An approach that abstracts from the actual strategy of an individual algorithm and can therefore be applied to any other form of machine learning.
  • None of these
Q19 | Inductive logic programming is
  • A class of learning algorithms that try to derive a Prolog program from examples*
  • A table with n independent attributes can be seen as an n- dimensional space.
  • A prediction made using an extremely simple method, such as always predicting the same output.
  • None of these
Q20 | Multi-dimensional knowledge is
  • A class of learning algorithms that try to derive a Prolog program from examples
  • A table with n independent attributes can be seen as an n- dimensional space
  • A prediction made using an extremely simple method, such as always predicting the same output.
  • None of these
Q21 | Naive prediction is
  • A class of learning algorithms that try to derive a Prolog program from examples
  • A table with n independent attributes can be seen as an n- dimensional space.
  • A prediction made using an extremely simple method, such as always predicting the same output.
  • None of these
Q22 | Knowledge is referred to
  • Non-trivial extraction of implicit previously unknown and potentially useful information from dat(A)
  • Set of columns in a database table that can be used to identify each record within this table uniquely.
  • collection of interesting and useful patterns in a database
  • none of these
Q23 | Node is
  • A component of a network
  • In the context of KDD and data mining, this refers to random errors in a database table.
  • One of the defining aspects of a data warehouse
  • None of these
Q24 | Projection pursuit is
  • The result of the application of a theory or a rule in a specific case
  • One of several possible enters within a database table that is chosen by the designer as the primary means of accessing the data in the table.
  • Discipline in statistics that studies ways to find the most interesting projections of multi-dimensional spaces
  • None of these
Q25 | Statistical significance is
  • The science of collecting, organizing, and applying numerical facts
  • Measure of the probability that a certain hypothesis is incorrect given certain observations.
  • One of the defining aspects of a data warehouse, which is specially built around all the existing applications of the operational dat(A)
  • None of these