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.
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
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.
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
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
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
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
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
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
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.
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.