Data Mining Set 2
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This set of Data Mining Multiple Choice Questions & Answers (MCQs) focuses on Data Mining Set 2
Q1 | 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
Q2 | 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
Q3 | 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
Q4 | 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 subset of another-column.
- none of these
Q5 | 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
Q6 | 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 subset of another-column
- none of these
Q7 | KDD (Knowledge Discovery in Databases) is referred to
- non-trivial extraction of implicit previously unknown and potentially useful information from data
- 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
Q8 | 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
Q9 | 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
Q10 | 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
Q11 | Knowledge is referred to
- non-trivial extraction of implicit previously unknown and potentially useful information from data
- 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
Q12 | 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
Q13 | 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
Q14 | 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
Q15 | 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
Q16 | 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 data
- none of these
Q17 | 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
Q18 | Prediction 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
Q19 | Query tools are
- a reference to the speed of an algorithm, which is quadratically dependent on the size of the data
- attributes of a database table that can take only numerical values.
- tools designed to query a database.
- none of these
Q20 | Operational database is
- a measure of the desired maximal complexity of data mining algorithms
- a database containing volatile data used for the daily operation of an organization
- relational database management system
- none of these
Q21 | ...................... is an essential process where intelligent methods are applied to extract data patterns.
- data warehousing
- data mining
- text mining
- data selection
Q22 | Which of the following is not a data mining functionality?
- characterization and discrimination
- classification and regression
- selection and interpretation
- clustering and analysis
Q23 | ............................. is a summarization of the general characteristics or features of a target class of data.
- data characterization
- data classification
- data discrimination
- data selection
Q24 | ............................. is a comparison of the general features of the target class data objects against the general features of objects from one or multiple contrasting classes.
- data characterization
- data classification
- data discrimination
- data selection
Q25 | Strategic value of data mining is ......................
- cost-sensitive
- work-sensitive
- time-sensitive
- technical-sensitive