Deck 2: Data Mining, Learning, and Knowledge Engineering

Question 1

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 1

it automatically maps an external signal space into a system\s internal representational space. they are useful in the performance of classification tasks

Question 2

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 2

the learning algorithmic analyzes the examples on a systematic basis and makes incremental adjustments to the theory that is learned

Question 3

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 3

the process of finding the right formal representation of a certain body of knowledge in order to represent it in a knowledge-based system

Question 4

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 subset of another-column.
D)none of these

Question 5

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

Question 6

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 subset of another-column
D)none of these

Question 7

KDD (Knowledge Discovery in Databases) is referred to

A)non-trivial extraction of implicit previously unknown and potentially useful information from data
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

Question 8

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

Question 9

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

Question 10

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

Question 11

Knowledge is referred to

A)non-trivial extraction of implicit previously unknown and potentially useful information from data
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

Question 12

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

Question 13

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

Question 14

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

Question 15

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

Question 16

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 data
D)none of these

Question 17

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

Question 18

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

Question 19

Query tools are

A)a reference to the speed of an algorithm, which is quadratically dependent on the size of the data
B)attributes of a database table that can take only numerical values.
C)tools designed to query a database.
D)none of these

Question 20

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

Question 21

...................... is an essential process where intelligent methods are applied to extract data patterns.

A)data warehousing
B)data mining
C)text mining
D)data selection

Question 22

Which of the following is not a data mining functionality?

A)characterization and discrimination
B)classification and regression
C)selection and interpretation
D)clustering and analysis

Question 23

............................. is a summarization of the general characteristics or features of a target class of data.

A)data characterization
B)data classification
C)data discrimination
D)data selection

Question 24

............................. 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.

A)data characterization
B)data classification
C)data discrimination
D)data selection

Question 25

Strategic value of data mining is ......................

A)cost-sensitive
B)work-sensitive
C)time-sensitive
D)technical-sensitive