400+ Data Mining and Data Warehouse Solved MCQs

301.

Which is not the type of attribute used in distance measure?

A. ordinal
B. nominal
C. binay
D. rank
Answer» D. rank
302.

_____ method is used to find the distance between two objects represented by numerical attributes.

A. euclidean distance
B. minkowski distance
C. manhattan distance
D. all of these
Answer» D. all of these
303.

Contingency table is prepared for _______ attribute data.

A. ordinal
B. nominal
C. binay
D. integer
Answer» C. binay
304.

Which are the applications of proximity measures?

A. classification
B. clustering
C. knn classifier
D. all of these
Answer» D. all of these
305.

_________ matrix represents the distance between all objects in the dataset

A. confusion
B. dissimilarity
C. similarity
D. square
Answer» B. dissimilarity
306.

If o1 and o2 are two objects and distance between these objects is zero then it means_____

A. o1 and o2 are totally similar
B. o1 and o2 are totally dissimilar
C. o1 and o2 are similar
D. o1 and o2 are partially dissimilar
Answer» A. o1 and o2 are totally similar
307.

Identify the correct subtype of Binary attribute.

A. ordinal
B. asymmetric
C. symmetric
D. both b and c
Answer» D. both b and c
308.

_____ Lower when objects are more alike.

A. dissimilarity
B. recall
C. similarity
D. accuracy
Answer» A. dissimilarity
309.

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
Answer» A. It uses machine-learning techniques. Here program can learn from past experience and adapt themselves to new situations
310.

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
Answer» B. Computational procedure that takes some value as input and produces some value as output
311.

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
Answer» A. Additional acquaintance used by a learning algorithm to facilitate the learning process
312.

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
Answer» B. A neural network that makes use of a hidden layer
313.

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
Answer» A. A class of learning algorithm that tries to find an optimum classification of a set of examples using the probabilistic theory.
314.

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
Answer» B. Any mechanism employed by a learning system to constrain the search space of a hypothesis.
315.

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
Answer» 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.
316.

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
Answer» A. This takes only two values. In general, these values will be 0 and 1 and they can be coded as one bit
317.

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
Answer» B. The natural environment of a certain species
318.

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
Answer» C. Systems that can be used without knowledge of internal operations
319.

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
Answer» C. Science of making machines performs tasks that would require intelligence when performed by humans
320.

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
Answer» 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
321.

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
Answer» B. The number of different values that a given attribute can take
322.

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
Answer» 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
323.

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
Answer» A. A subdivision of a set of examples into a number of classes
324.

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
Answer» B. Measure of the accuracy, of the classification of a concept that is given by a certain theory
325.

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
Answer» A. Group of similar objects that differ significantly from other objects
326.

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 extract
Answer» C. Symbolic representation of facts or ideas from which information can potentially be extract
327.

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
Answer» A. Complete
328.

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» B. Consistent
329.

Classification task referred to

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
Answer» C. The task of assigning a classification to a set of examples
330.

Database is

A. Large collection of data mostly stored in a computer system
B. The removal of noise errors and incorrect input from a database
C. The systematic description of the syntactic structure of a specific database. It describes the structure of the attributes the tables and foreign key relationships.
D. None of these
Answer» A. Large collection of data mostly stored in a computer system
331.

Data cleaning is

A. Large collection of data mostly stored in a computer system
B. The removal of noise errors and incorrect input from a database
C. The systematic description of the syntactic structure of a specific database. It describes the structure of the attributes the tables and foreign key relationships.
D. None of these
Answer» B. The removal of noise errors and incorrect input from a database
332.

Data dictionary is

A. Large collection of data mostly stored in a computer system
B. The removal of noise errors and incorrect input from a database
C. The systematic description of the syntactic structure of a specific database. It describes the structure of the attributes the tables and foreign key relationships.
D. None of these
Answer» C. The systematic description of the syntactic structure of a specific database. It describes the structure of the attributes the tables and foreign key relationships.
333.

Data mining is

A. The actual discovery phase of a knowledge discovery process
B. The stage of selecting the right data for a KDD process
C. A subject-oriented integrated time- variant non-volatile collection of data in support of management
D. None of these
Answer» A. The actual discovery phase of a knowledge discovery process
334.

Data selection is

A. The actual discovery phase of a knowledge discovery process
B. The stage of selecting the right data for a KDD process
C. A subject-oriented integrated time- variant non-volatile collection of data in support of management
D. None of these
Answer» B. The stage of selecting the right data for a KDD process
335.

Data warehouse is

A. The actual discovery phase of a knowledge discovery process
B. The stage of selecting the right data for a KDD process
C. A subject-oriented integrated time- variant non-volatile collection of data in support of management
D. None of these
Answer» C. A subject-oriented integrated time- variant non-volatile collection of data in support of management
336.

Coding 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
Answer» B. Operations on a database to transform or simplify data in order to prepare it for a machine-learning algorithm
337.

DB/2 is

A. A family of relational database manage- ment systems marketed by IBM
B. Interactive systems that enable decision makers to use databases and models on a computer in order to solve ill- structured problems
C. It consists of nodes and branches starting from a single root node. Each node represents a test, or decision.
D. None of these
Answer» A. A family of relational database manage- ment systems marketed by IBM
338.

Decision support systems (DSS) is

A. A family of relational database management systems marketed by IBM
B. Interactive systems that enable decision makers to use databases and models on a computer in order to solve ill- structured problems
C. It consists of nodes and branches starting from a single root node. Each node represents a test, or decision.
D. None of these
Answer» B. Interactive systems that enable decision makers to use databases and models on a computer in order to solve ill- structured problems
339.

Decision trees is

A. A family of relational database management systems marketed by IBM
B. Interactive systems that enable decision makers to use databases and models on a computer in order to solve ill- structured problems
C. It consists of nodes and branches starting from a single root node. Each node represents a test, or decision.
D. None of these
Answer» C. It consists of nodes and branches starting from a single root node. Each node represents a test, or decision.
340.

Deep knowledge referred to

A. It is hidden within a database and can only be recovered if one is given certain clues (an example IS encrypted information)
B. The process of executing implicit previously unknown and potentially useful information from dat(A)
C. An extremely complex molecule that occurs in human chromosomes and that carries genetic information in the form of genes.
D. None of these
Answer» A. It is hidden within a database and can only be recovered if one is given certain clues (an example IS encrypted information)
341.

Discovery is

A. It is hidden within a database and can only be recovered if one is given certain clues (an example IS encrypted information).
B. The process of executing implicit previously unknown and potentially useful information from dat(A)
C. An extremely complex molecule that occurs in human chromosomes and that carries genetic information in the form of genes.
D. None of these
Answer» B. The process of executing implicit previously unknown and potentially useful information from dat(A)
342.

DNA (Deoxyribonucleic acid)

A. It is hidden within a database and can only be recovered if one is given certain clues (an example IS encrypted information).
B. The process of executing implicit previously unknown and potentially useful information from dat (A)
C. An extremely complex molecule that occurs in human chromosomes and that carries genetic information in the form of genes.
D. None of these
Answer» C. An extremely complex molecule that occurs in human chromosomes and that carries genetic information in the form of genes.
343.

Enrichment is

A. A stage of the KDD process in which new data is added to the existing selection
B. The process of finding a solution for a problem simply by enumerating all possible solutions according to some pre-defined order and then testing them.
C. The distance between two points as calculated using the Pythagoras theorem.
D. None of these
Answer» A. A stage of the KDD process in which new data is added to the existing selection
344.

Enumeration is referred to

A. A stage of the KDD process in which new data is added to the existing selection.
B. The process of finding a solution for a problem simply by enumerating all possible solutions according to some pre-defined order and then testing them
C. The distance between two points as calculated using the Pythagoras theorem.
D. None of these
Answer» B. The process of finding a solution for a problem simply by enumerating all possible solutions according to some pre-defined order and then testing them
345.

Euclidean distance measure is

A. A stage of the KDD process in which new data is added to the existing selection.
B. The process of finding a solution for a problem simply by enumerating all possible solutions according to some pre-defined order and then testing them.
C. The distance between two points as calculated using the Pythagoras theo- rem
D. None of these
Answer» C. The distance between two points as calculated using the Pythagoras theo- rem
346.

Heuristic is

A. A set of databases from different vendors, possibly using different database paradigms
B. An approach to a problem that is not guaranteed to work but performs well in most cases.
C. Information that is hidden in a database and that cannot be recovered by a simple SQL query.
D. None of these
Answer» B. An approach to a problem that is not guaranteed to work but performs well in most cases.
347.

Heterogeneous databases referred to

A. A set of databases from different vendors, possibly using different database paradigms
B. An approach to a problem that is not guaranteed to work but performs well in most cases.
C. Information that is hidden in a database and that cannot be recovered by a simple SQL query.
D. None of these
Answer» A. A set of databases from different vendors, possibly using different database paradigms
348.

Hidden knowledge referred to

A. A set of databases from different vendors, possibly using different database paradigms
B. An approach to a problem that is not guaranteed to work but performs well in most cases.
C. Information that is hidden in a database and that cannot be recovered by a simple SQL query.
D. None of these
Answer» C. Information that is hidden in a database and that cannot be recovered by a simple SQL query.
349.

Hybrid is

A. Combining different types of method or information
B. Approach to the design of learning algorithms that is structured along the lines of the theory of evolution.
C. Decision support systems that contain an Information base filled with the knowledge of an expert formulated in terms of if-then rules.
D. None of these
Answer» A. Combining different types of method or information
350.

Evolutionary computation is

A. Combining different types of method or information
B. Approach to the design of learning algorithms that is structured along the lines of the theory of evolution.
C. Decision support systems that contain an Information base filled with the knowledge of an expert formulated in terms of if-then rules.
D. None of these
Answer» B. Approach to the design of learning algorithms that is structured along the lines of the theory of evolution.
351.

Expert systems

A. Combining different types of method or information
B. Approach to the design of learning algorithms that is structured along the lines of the theory of evolution.
C. Decision support systems that contain an Information base filled with the knowledge of an expert formulated in terms of if-then rules
D. None of these
Answer» C. Decision support systems that contain an Information base filled with the knowledge of an expert formulated in terms of if-then rules
352.

Extendible architecture is

A. Modular design of a software application that facilitates the integration of new modules
B. Showing a universal law or rule to be invalid by providing a counter example
C. A set of attributes in a database table that refers to data in another table
D. None of these
Answer» A. Modular design of a software application that facilitates the integration of new modules
353.

Falsification is

A. Modular design of a software application that facilitates the integration of new modules
B. Showing a universal law or rule to be invalid by providing a counter example
C. A set of attributes in a database table that refers to data in another table
D. None of these
Answer» B. Showing a universal law or rule to be invalid by providing a counter example
354.

Foreign key is

A. Modular design of a software application that facilitates the integration of new modules
B. Showing a universal law or rule to be invalid by providing a counter example
C. A set of attributes in a database table that refers to data in another table
D. None of these
Answer» C. A set of attributes in a database table that refers to data in another table
355.

Hybrid learning is

A. Machine-learning involving different techniques
B. The learning algorithmic analyzes the examples on a systematic basis and makes incremental adjustments to the theory that is learned
C. Learning by generalizing from examples
D. None of these
Answer» A. Machine-learning involving different techniques
356.

Incremental learning referred to

A. Machine-learning involving different techniques
B. The learning algorithmic analyzes the examples on a systematic basis and makes incremental adjustments to the theory that is learned
C. Learning by generalizing from examples
D. None of these
Answer» B. The learning algorithmic analyzes the examples on a systematic basis and makes incremental adjustments to the theory that is learned
357.

Information content is

A. The amount of information with in data as opposed to the amount of redundancy or noise
B. One of the defining aspects of a data warehouse
C. Restriction that requires data in one column of a database table to the a sub- set of another-column.
D. None of these
Answer» A. The amount of information with in data as opposed to the amount of redundancy or noise
358.

Inclusion dependencies

A. The amount of information with in data as opposed to the amount of redundancy or noise
B. One of the defining aspects of a data warehouse
C. Restriction that requires data in one column of a database table to the a sub- set of another-column
D. None of these
Answer» C. Restriction that requires data in one column of a database table to the a sub- set of another-column
359.

KDD (Knowledge Discovery in Databases) is referred to

A. Non-trivial extraction of implicit previously unknown and potentially useful information from dat(A)
B. Set of columns in a database table that can be used to identify each record within this table uniquely.
C. collection of interesting and useful patterns in a database
D. none of these
Answer» A. Non-trivial extraction of implicit previously unknown and potentially useful information from dat(A)
360.

Key is referred to

A. Non-trivial extraction of implicit previously unknown and potentially useful information from dat(A)
B. Set of columns in a database table that can be used to identify each record within this table uniquely
C. collection of interesting and useful patterns in a database
D. none of these
Answer» B. Set of columns in a database table that can be used to identify each record within this table uniquely
361.

Inductive learning is

A. Machine-learning involving different techniques
B. The learning algorithmic analyzes the examples on a systematic basis and makes incremental adjustments to the theory that is learned
C. Learning by generalizing from examples
D. None of these
Answer» C. Learning by generalizing from examples
362.

Integrated is

A. The amount of information with in data as opposed to the amount of redundancy or noise
B. One of the defining aspects of a data warehouse
C. Restriction that requires data in one column of a database table to the a sub- set of another-column.
D. None of these
Answer» B. One of the defining aspects of a data warehouse
363.

Knowledge engineering is

A. The process of finding the right formal representation of a certain body of knowledge in order to represent it in a knowledge-based system
B. It automatically maps an external signal space into a system’s internal representational space. They are useful in the performance of classification tasks.
C. 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.
D. None of these
Answer» A. The process of finding the right formal representation of a certain body of knowledge in order to represent it in a knowledge-based system
364.

Kohonen self-organizing map referred to

A. The process of finding the right formal representation of a certain body of knowledge in order to represent it in a knowledge-based system
B. It automatically maps an external signal space into a system’s internal representational space. They are useful in the performance of classification tasks
C. 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.
D. None of these
Answer» B. It automatically maps an external signal space into a system’s internal representational space. They are useful in the performance of classification tasks
365.

Learning is

A. The process of finding the right formal representation of a certain body of knowledge in order to represent it in a knowledge-based system
B. It automatically maps an external signal space into a system’s internal representational space. They are useful in the performance of classification tasks.
C. 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.
D. None of these
Answer» C. 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.
366.

Learning algorithm referrers to

A. An algorithm that can learn
B. A sub-discipline of computer science that deals with the design and implementation of learning algorithms.
C. 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.
D. None of these
Answer» A. An algorithm that can learn
367.

Meta-learning is

A. An algorithm that can learn
B. A sub-discipline of computer science that deals with the design and implementation of learning algorithms.
C. 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.
D. None of these
Answer» C. 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.
368.

Machine learning is

A. An algorithm that can learn
B. A sub-discipline of computer science that deals with the design and implementation of learning algorithms.
C. An approach that abstracts from the actual strategy of an individual algorithm and can therefore be applied to any other form of machine learning.
D. None of these
Answer» B. A sub-discipline of computer science that deals with the design and implementation of learning algorithms.
369.

Inductive logic programming is

A. A class of learning algorithms that try to derive a Prolog program from examples*
B. A table with n independent attributes can be seen as an n- dimensional space.
C. A prediction made using an extremely simple method, such as always predicting the same output.
D. None of these
Answer» A. A class of learning algorithms that try to derive a Prolog program from examples*
370.

Multi-dimensional knowledge is

A. A class of learning algorithms that try to derive a Prolog program from examples
B. A table with n independent attributes can be seen as an n- dimensional space
C. A prediction made using an extremely simple method, such as always predicting the same output.
D. None of these
Answer» B. A table with n independent attributes can be seen as an n- dimensional space
371.

Naive prediction is

A. A class of learning algorithms that try to derive a Prolog program from examples
B. A table with n independent attributes can be seen as an n- dimensional space.
C. A prediction made using an extremely simple method, such as always predicting the same output.
D. None of these
Answer» C. A prediction made using an extremely simple method, such as always predicting the same output.
372.

Knowledge is referred to

A. Non-trivial extraction of implicit previously unknown and potentially useful information from dat(A)
B. Set of columns in a database table that can be used to identify each record within this table uniquely.
C. collection of interesting and useful patterns in a database
D. none of these
Answer» C. collection of interesting and useful patterns in a database
373.

Node 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
Answer» A. A component of a network
374.

Projection pursuit is

A. The result of the application of a theory or a rule in a specific case
B. 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.
C. Discipline in statistics that studies ways to find the most interesting projections of multi-dimensional spaces
D. None of these
Answer» C. Discipline in statistics that studies ways to find the most interesting projections of multi-dimensional spaces
375.

Statistical significance is

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
Answer» B. Measure of the probability that a certain hypothesis is incorrect given certain observations.
376.

Prediction is

A. The result of the application of a theory or a rule in a specific case
B. 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.
C. Discipline in statistics that studies ways to find the most interesting projections of multi-dimensional spaces.
D. None of these
Answer» A. The result of the application of a theory or a rule in a specific case
377.

Primary key is

A. The result of the application of a theory or a rule in a specific case
B. 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
C. Discipline in statistics that studies ways to find the most interesting projections of multi-dimensional spaces.
D. None of these
Answer» B. 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
378.

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
Answer» B. In the context of KDD and data mining, this refers to random errors in a database table.
379.

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
Answer» A. A reference to the speed of an algorithm, which is quadratically dependent on the size of the dat(A)
380.

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
Answer» C. Tools designed to query a database.
381.

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
Answer» A. A programming language based on logic
382.

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
Answer» B. A computer where each processor has its own operating system, its own memory, and its own hard disk
383.

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
Answer» C. Describes the structure of the contents of a database
384.

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
Answer» A. A measure of the desired maximal complexity of data mining algorithms
385.

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
Answer» B. A database containing volatile data used for the daily operation of an organization
386.

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
Answer» C. Relational database management system
387.

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.
Answer» A. General class of approaches to a problem.
388.

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.
Answer» C. Structures in a database those are statistically relevant
389.

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.
Answer» B. Performing several computations simultaneously
390.

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.
Answer» D. Simple forerunner of modern neural networks, without hidden layers.
391.

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
Answer» B. The information stored in a database that can be, retrieved with a single query.
392.

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
Answer» A. The science of collecting, organizing, and applying numerical facts
393.

Subject orientation

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
Answer» C. One of the defining aspects of a data warehouse, which is specially built around all the existing applications of the operational dat(A)
394.

Search space

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 understandable for humans
D. None of these
Answer» A. The large set of candidate solutions possible for a problem
395.

Transparency

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
Answer» C. Worth of the output of a machine- learning program that makes it under- standable for humans
396.

Quantitative attributes 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
Answer» B. Attributes of a database table that can take only numerical values.
397.

Unsupervised algorithms

A. It do not need the control of the human operator during their execution.
B. An arrow in a multi-dimensional space. It is a quantity usually characterized by an ordered set of scalars.
C. The validation of a theory on the basis of a finite number of examples.
D. None of these
Answer» A. It do not need the control of the human operator during their execution.
398.

Vector

A. It do not need the control of the human operator during their execution.
B. An arrow in a multi-dimensional space. It is a quantity usually characterized by an ordered set of scalars.
C. The validation of a theory on the basis of a finite number of examples.
D. None of these
Answer» B. An arrow in a multi-dimensional space. It is a quantity usually characterized by an ordered set of scalars.
399.

Verification

A. It does not need the control of the human operator during their execution.
B. An arrow in a multi-dimensional space. It is a quantity usually characterized by an ordered set of scalars.
C. The validation of a theory on the basis of a finite number of examples
D. None of these
Answer» C. The validation of a theory on the basis of a finite number of examples
400.

Visualization techniques are

A. A class of graphic techniques used to visualize the contents of a database
B. The division of a certain space into various areas based on guide points.
C. A branch that connects one node to another
D. None of these
Answer» A. A class of graphic techniques used to visualize the contents of a database
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