1
Chapter 1
Multiple Choice Questions
(1.1)
1. The process of forming general concept definitions from examples of concepts to be learned.
a. deduction
b. abduction
c. induction
d. conjunction
2. Data mining is best described as the process of
a. identifying patterns in data.
b. deducing relationships in data.
c. representing data.
d. simulating trends in data.
(1.2)
3. Computers are best at learning
a. facts.
b. Concepts.
c. Procedures.
d. Principles.
, 2
4. Like the probabilistic view, the ________ view allows us to associate a probability of
membership with each classification.
a. exemplar
b. deductive
c. classical
d. inductive
5. Data used to build a data mining model.
a. validation data
b. training data
c. test data
d. hidden data
6. Supervised learning and unsupervised clustering both require at least one
a. hidden attribute.
b. output attribute.
c. input attribute.
d. categorical attribute.
7. Supervised learning differs from unsupervised clustering in that supervised learning requires
a. at least one input attribute.
b. input attriutes to be categorical.
c. at least one output attribute.
d. ouput attriubutes to be categorical.
, 3
8. Which of the following is a valid production rule for the decision tree below?
a. IF Business Appointment = No & Temp above 70 = No
THEN Decision = wear slacks
b. IF Business Appointment = Yes & Temp above 70 = Yes
THEN Decision = wear shorts
c. IF Temp above 70 = No
THEN Decision = wear shorts
d. IF Business Appointment= No & Temp above 70 = No
THEN Decision = wear jeans
(1.3)
9. Database query is used to uncover this type of knowledge.
a. deep
b. hidden
c. shallow
d. multidimensional
, 4
10. A statement to be tested.
a. theory
b. procedure
c. principle
d. hypothesis
(1.4)
11. A person trained to interact with a human expert in order to capture their knowledge.
a. knowledge programmer
b. knowledge developer
c. knowledge engineer
d. knowledge extractor
(1.5)
12. Which of the following is not a characteristic of a data warehouse?
a. contains historical data
b. designed for decision support
c. stores data in normalized tables
d. promotes data redundancy
13. A structure designed to store data for decision support.
a. operational database
b. flat file
c. decision tree
d. data warehouse
Chapter 1
Multiple Choice Questions
(1.1)
1. The process of forming general concept definitions from examples of concepts to be learned.
a. deduction
b. abduction
c. induction
d. conjunction
2. Data mining is best described as the process of
a. identifying patterns in data.
b. deducing relationships in data.
c. representing data.
d. simulating trends in data.
(1.2)
3. Computers are best at learning
a. facts.
b. Concepts.
c. Procedures.
d. Principles.
, 2
4. Like the probabilistic view, the ________ view allows us to associate a probability of
membership with each classification.
a. exemplar
b. deductive
c. classical
d. inductive
5. Data used to build a data mining model.
a. validation data
b. training data
c. test data
d. hidden data
6. Supervised learning and unsupervised clustering both require at least one
a. hidden attribute.
b. output attribute.
c. input attribute.
d. categorical attribute.
7. Supervised learning differs from unsupervised clustering in that supervised learning requires
a. at least one input attribute.
b. input attriutes to be categorical.
c. at least one output attribute.
d. ouput attriubutes to be categorical.
, 3
8. Which of the following is a valid production rule for the decision tree below?
a. IF Business Appointment = No & Temp above 70 = No
THEN Decision = wear slacks
b. IF Business Appointment = Yes & Temp above 70 = Yes
THEN Decision = wear shorts
c. IF Temp above 70 = No
THEN Decision = wear shorts
d. IF Business Appointment= No & Temp above 70 = No
THEN Decision = wear jeans
(1.3)
9. Database query is used to uncover this type of knowledge.
a. deep
b. hidden
c. shallow
d. multidimensional
, 4
10. A statement to be tested.
a. theory
b. procedure
c. principle
d. hypothesis
(1.4)
11. A person trained to interact with a human expert in order to capture their knowledge.
a. knowledge programmer
b. knowledge developer
c. knowledge engineer
d. knowledge extractor
(1.5)
12. Which of the following is not a characteristic of a data warehouse?
a. contains historical data
b. designed for decision support
c. stores data in normalized tables
d. promotes data redundancy
13. A structure designed to store data for decision support.
a. operational database
b. flat file
c. decision tree
d. data warehouse
