Classical

Data Mining - Data Mining MCQ

36:  

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

 
 

Option: C

Explanation :


37:  

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

 
 

Option: A

Explanation :


38:  

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

 
 

Option: C

Explanation :


39:  

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

 
 

Option: A

Explanation :


40:  

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

 
 

Option: B

Explanation :




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