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Data Mining: 

 

Data Mining is the process of extracting valuable information and discovering patterns in large data sets. It involves the methods at the intersection of statistics, machine learning and database systems. 

 

 

Data Mining Sample Questions:

 

 

Question 1: Inferring a model by labelled training of data is called?

 

A) Reinforcement learning 

B) Supervised learning

C) Unsupervised learning 

D) None of these

 

Answer: Supervised learning

Explanation: Supervised learning: machine learns by labelled training of data
Unsupervised learning: machine finds hidden pattern or structure in unlabeled data.
Reinforcement learning: reward based learning  

 

 

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Question 2: Self organising maps are based on:

 

A) Reinforcement learning 

B) Supervised learning 

C) Unsupervised learning 

D) None of these


Answer: Unsupervised learning 

Explanation: Machine would find hidden pattern in unlabeled data so, Unsupervised learning. 

 

 

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Question 3: Data mining is not involved in which of the following?

 

A) Knowledge extraction 

B) Data archaeology 

C) Data exploration 

D) Data transformation

Answer: Data transformation

Explanation: Data mining is involved in the following:
Knowledge extraction 
Data archaeology 
Data exploration 

 

 

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Question 4:  Issues that are considered before investing in Data Mining are?

 

A) Functionality

B) Compatibility 

C) Both of these

D) None of these


Answer: Both of these

Explanation: Issues that are considered before investing in Data Mining are:
Functionality 
Compatibility
Vendor consideration 

 

 

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Question 5: Where is the SET concept used?

 

A) Hierarchical model

B) Distributed Model

C) Relational Model

D) None of these

 

Answer: None of these

Explanation: SET concept is used in Network Model

 

 

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Question 6: Clustering technique is required in which of the merging approaches?


 

A) Naive Bayes

B) Hierarchical

C) Partitioned 

D) None of these


Answer: Hierarchical

Explanation: The nodes having similar characteristics are merged together afer 

 

 

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Question 7: How many categories of functions are involved in Data Mining?

 

A) 3

B) 4

C) 5

D) None of these

 

Answer: None of these

Explanation: There are 2 category of functions that are involved in data mining: 
Descriptive 
Classification and Prediction

 

 

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Question 8: For integration of heterogeneous databases, data warehousing provides how many approaches?

 

A) 1

B) 2

C) 3

D) 4

 

Answer: 2

Explanation: For integrating heterogeneous databases there are two approaches:
Update Driven Approach
Query Driven Approach 

 

 

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Question 9: Class under study in data characterization is called?

 

A) Study Class

B) Target Class

C) Final Class 

D) None of these


Answer: Target Class

Explanation: Data characterization is summarizing data of class under study and it is called Target Class.

 

 

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Question 10: What is the full form of DMQL?

 

A) Data Management Query Language 

B) Data Mining Query Language

C) Database Mining Query Language 

D) None of these

 

Answer: Data Mining Query Language 

Explanation: DMQL stands for Data Mining Query Language and was proposed by Han, Fu, Wan for DBMiner data mining system.


 

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