ALL CHAPTERS COVERED
, Questions for 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 structure in data.
b. deducing relationships in data.
c. representing data.
d. simulating trends in data.
3. Data _______ or _______analytics is defined as the process of extracting meaninful knowledge from
data.
a. mining, machine
b. discovery, knowledge
c. mining, scientific
d. science, data
(1.2)
4. Computers are best at learning
a. facts.
b. concepts.
c. procedures.
d. principles.
5. 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
,6. Data used to build a data mining model.
a. validation data
b. training data
c. test data
d. hidden data
7. Suppose the following rule is derived from a data set of 100 individuals.
IF age < 25 and gender = male THEN life insurance policy = no
Rule precision: 80%
Rule coverage: 50%
What can we conclude from this rule?
a. 80% of all males who are less than 25 do not have life insurance.
b. 50 of the 100 individuals are males less than 25 years of age.
c. 40 individuals satisfy both the rule antecedent and consequent conditions.
d. All of the above statements are correct.
8. Supervised learning differs from unsupervised clustering in that supervised learning requires
a. at least one input attribute.
b. input attributes to be categorical.
c. at least one output attribute.
d. ouput attriubutes to be categorical.
9. Which of the following is a valid rule for the decision tree below?
Business
Appoint-
ment?
No Yes
Decision =
Temp wear slacks
above
70?
No Yes
Decision = Decision =
wear jeans wear shorts
, 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)
10. Database query is used to uncover this type of knowledge.
a. deep
b. hidden
c. shallow
d. multidimensional
11. A statement to be tested.
a. theory
b. procedure
c. principle
d. hypothesis
(1.4)
12. 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
13. Expert systems are able to _____ the problem solving methods of a human expert.
a. emulate
b. develop
c. diagnose
d. evaulate
(1.5)
, Questions for 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 structure in data.
b. deducing relationships in data.
c. representing data.
d. simulating trends in data.
3. Data _______ or _______analytics is defined as the process of extracting meaninful knowledge from
data.
a. mining, machine
b. discovery, knowledge
c. mining, scientific
d. science, data
(1.2)
4. Computers are best at learning
a. facts.
b. concepts.
c. procedures.
d. principles.
5. 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
,6. Data used to build a data mining model.
a. validation data
b. training data
c. test data
d. hidden data
7. Suppose the following rule is derived from a data set of 100 individuals.
IF age < 25 and gender = male THEN life insurance policy = no
Rule precision: 80%
Rule coverage: 50%
What can we conclude from this rule?
a. 80% of all males who are less than 25 do not have life insurance.
b. 50 of the 100 individuals are males less than 25 years of age.
c. 40 individuals satisfy both the rule antecedent and consequent conditions.
d. All of the above statements are correct.
8. Supervised learning differs from unsupervised clustering in that supervised learning requires
a. at least one input attribute.
b. input attributes to be categorical.
c. at least one output attribute.
d. ouput attriubutes to be categorical.
9. Which of the following is a valid rule for the decision tree below?
Business
Appoint-
ment?
No Yes
Decision =
Temp wear slacks
above
70?
No Yes
Decision = Decision =
wear jeans wear shorts
, 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)
10. Database query is used to uncover this type of knowledge.
a. deep
b. hidden
c. shallow
d. multidimensional
11. A statement to be tested.
a. theory
b. procedure
c. principle
d. hypothesis
(1.4)
12. 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
13. Expert systems are able to _____ the problem solving methods of a human expert.
a. emulate
b. develop
c. diagnose
d. evaulate
(1.5)
