Deck 25: Introduction to Data Mining

Question 1

Relate data mining algorithms to goals.
Data gathered from various telecommunication companies (e.g. cable, phone,
Internet service providers) and utility companies (electric, fuel, etc.) were merged into
One data warehouse. Suppose the goal of data mining using this data warehouse was to
Predict whether a household's telecommunication needs will increase, decrease or stay
The same over the next year. What technique might be most appropriate for achieving
This goal?

A) Neural network.
B) Supervised problem.
C) Tree model.
D) Nodal network.
E) None of the above.

Answer 1

C

Question 2

Understand the data mining process.
Information about variables, such as variable definitions as well as how and when data
Were collected, is collectively called

A) superdata.
B) metadata.
C) extradata.
D) cases.
E) none of the above.

Answer 2

B

Question 3

Recognize classification and regression problems in data mining.
Data gathered from home improvement retailers (e.g. Lowe's, Home Depot, etc.) and
Publishing companies (magazines, books, etc.) were merged into one data warehouse.
Suppose data mining is used to determine whether or not a household subscribes to
Magazines about home and garden. In data mining this is referred to as what type of
Problem?

A) Regression.
B) Transactional.
C) Unsupervised.
D) Classification.
E) None of the above.

Answer 3

D

Question 4

Understand the data mining process.
Data not used in building the model but used to evaluate the performance of the
Model is known as

A) the terminal node.
B) the test set.
C) meta data.
D) the training set.
E) None of the above.

Question 5

Understand the data mining process.
Data used in a supervised problem to build the predictive model is known as

A) the terminal node.
B) the test set.
C) meta data.
D) the training set.
E) None of the above.

Question 6

Understand the data mining process.
Which is not a phase of the data mining process?

A) Business understanding.
B) Data preparation.
C) Modeling.
D) Deployment.
E) None of the above.

Question 7

Recognize classification and regression problems in data mining.
Data gathered from various automobile dealers (Toyota, BMW, etc.) and pro-
Environment organizations (e.g., Sierra Club) were merged into one data warehouse.
Suppose data mining is used to determine whether or not a customer would purchase a
Hybrid vehicle. In data mining this is referred to as what type of problem?

A) Regression.
B) Transactional.
C) Unsupervised.
D) Classification.
E) None of the above.

Question 8

Recognize classification and regression problems in data mining.
Data gathered from various automobile dealers (Toyota, BMW, etc.) and pro-
Environment organizations (e.g., Sierra Club) were merged into one data warehouse.
Suppose data mining is used to determine how important it is for a customer to purchase
A vehicle with a very low carbon footprint. In data mining this is referred to as what type
Of problem?

A) Regression.
B) Transactional.
C) Unsupervised.
D) Classification.
E) None of the above.

Question 9

Identify data mining algorithms.
Popular data mining tools inspired by models that tried to mimic the function of the
Brain are known as

A) Tree models.
B) Supervised problems.
C) Neural networks.
D) Nodal network.
E) None of the above.

Question 10

Relate data mining algorithms to goals.
Scanner data gathered from various supermarket chains were merged with data from
The travel industry (e.g., airlines, hotels, etc) into one data warehouse. Suppose the goal of
Data mining using this data warehouse is to predict whether a customer's expenditures on
International specialty food items would increase, decrease or stay the same in the next
Year. What technique might be most appropriate for achieving this goal?

A) Neural network.
B) Unsupervised problem.
C) Tree model.
D) Nodal network.
E) None of the above.

Question 11

Recognize classification and regression problems in data mining.
Data gathered from home improvement retailers (e.g. Lowe's, Home Depot, etc.) and
Publishing companies (magazines, books, etc.) were merged into one data warehouse.
Suppose data mining is used to determine how much a customer spends annually on
Energy efficient products. In data mining this is referred to as what type of problem?

A) Regression.
B) Transactional.
C) Unsupervised.
D) Classification.
E) None of the above.