Data Mining homework Help at TutorEye

## 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

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

Question 2: Self organising maps are based on:

A) Reinforcement learning

B) Supervised learning

C) Unsupervised learning

D) None of these

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

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

A) Knowledge extraction

B) Data archaeology

C) Data exploration

D) Data transformation

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

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

A) Functionality

B) Compatibility

C) Both of these

D) None of these

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

Question 5: Where is the SET concept used?

A) Hierarchical model

B) Distributed Model

C) Relational Model

D) None of these

Explanation: SET concept is used in Network Model

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

A) Naive Bayes

B) Hierarchical

C) Partitioned

D) None of these

Explanation: The nodes having similar characteristics are merged together afer

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

A) 3

B) 4

C) 5

D) None of these

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

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

A) 1

B) 2

C) 3

D) 4

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

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

A) Study Class

B) Target Class

C) Final Class

D) None of these

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

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

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