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

Accepted Answer

Kohonen self-organizing maps (SOMs) are a type of artificial neural network that is trained using unsupervised learning to produce a low-dimensional (typically two-dimensional), discretized representation of the input space of the training samples. This makes them particularly useful for visualization and classification tasks, as they can help to understand the structure of complex data by mapping it to a simpler, more interpretable form.

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

Accepted Answer

Incremental learning involves an algorithm analyzing examples systematically and making incremental adjustments to the theory it has learned, allowing it to adapt to new data over time.

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

Accepted Answer

Knowledge engineering is the process of creating rules and representations for knowledge-based systems, which involves finding the right formal representation of knowledge to be used in such systems.

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

Accepted Answer

Information content refers to the amount of actual information within data, distinguishing it from redundancy or noise, which do not contribute to the meaningful content of the data.

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

Accepted Answer

Inductive learning involves generalizing from specific examples to form broader concepts or rules.

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

Accepted Answer

Inclusion dependencies are constraints in databases where the set of values in one column (or a group of columns) of a table must be a subset of the set of values in another column (or a group of columns) in the same or a different table. This ensures referential integrity within the database.

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

Accepted Answer

KDD refers to the process of discovering useful information from large datasets, which involves the non-trivial extraction of implicit, previously unknown, and potentially useful information from data.

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

Accepted Answer

Learning involves acquiring the ability to perform a task that was previously unachievable, indicating a transition in capability.

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

Accepted Answer

Naive prediction refers to making forecasts based on very simple methods or assumptions, such as always predicting the most common outcome without analyzing the data in depth. This approach does not involve complex algorithms or models.

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

Accepted Answer

Learning algorithms are essentially algorithms that have the capability to learn from data. They adjust their operations or improve their performance based on the input data they are provided, without being explicitly programmed for every possible scenario.

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

Accepted Answer

Knowledge refers to the collection of interesting and useful patterns in a database, which aligns with the concept of extracting meaningful insights from data.

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

Accepted Answer

A node in the context of networks refers to any device or data point that can send, receive, or forward information over a network channel. Examples include computers, mobile devices, or other pieces of networking hardware.

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

Accepted Answer

Machine learning is a sub-discipline of computer science focused on designing and implementing algorithms that allow computers to learn from and make predictions or decisions based on data.

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

Accepted Answer

Projection pursuit is a statistical technique that involves finding the most "interesting" projections in multidimensional data. It aims to identify the projections that reveal the most structure or patterns within the data, which might not be visible in the original multidimensional space.

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

Accepted Answer

Inductive Logic Programming (ILP) is indeed a class of learning algorithms that focuses on deriving a logic program (often in the form of Prolog rules) from observed examples. This approach combines the techniques of machine learning with the formalisms of logic programming.

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

Accepted Answer

Statistical significance is a measure of the probability that a certain hypothesis is incorrect given certain observations. It is used in hypothesis testing to determine if the results of a study can be considered reliable or if they might have occurred by chance.

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

Accepted Answer

A table with n independent attributes can indeed be viewed as an n-dimensional space, where each dimension corresponds to one of the attributes. This concept is fundamental in areas such as database systems and data mining, where multi-dimensional analysis is often performed.

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

Accepted Answer

Prediction involves applying a theory or rule to a specific case to forecast an outcome or determine a result.

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

Accepted Answer

Query tools are specifically designed for querying databases, allowing users to search for and retrieve information from a database efficiently. Choices A and B describe algorithm complexity and data attributes, respectively, which are unrelated to the concept of query tools.

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

Accepted Answer

Operational databases are designed to manage and store the data related to the daily operations of an organization. They are characterized by their ability to handle large volumes of dynamic data in real-time or near-real-time.

Quiz 2: Data Mining, Learning, and Knowledge Engineering

Kohonen self-organizing map referred to

Incremental learning referred to

Knowledge engineering is

Information content is

Inductive learning is

Inclusion dependencies

KDD (Knowledge Discovery in Databases) is referred to

Learning is

Naive prediction is

Learning algorithm referrers to

Knowledge is referred to

Node is

Machine learning is

Projection pursuit is

Inductive logic programming is

Statistical significance is

Multi-dimensional knowledge is

Prediction is

Query tools are

Operational database is