ITS632 Golden Gate University San Francisco Data Mining Exam Questions

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1.True / False

Our use of association analysis will yield the same frequent itemsets and strong association rules whether a specific item occurs once or three times in an individual transaction.

ANSWER:

2.True / False

A density-based clustering algorithm can generate non-globular clusters.

ANSWER:

3.True / False

The k-means clustering algorithm will automatically find the best value of k as part of its normal operation.

ANSWER:

4. True / False

In association rule mining the generation of the frequent itemsets is the computational intensive step.

ANSWER:

5. In the following figure, there are two clusters. They are connected by a line which represents the distance used to determine inter-cluster similarity.

Which inter-cluster similarity metric does this line represent?

a. Min

b. Max

c. Group Average

d. Distance between centroids

ANSWER (JUST INDICATE THE LETTER OF YOUR RESPONSE – DO NOT USE WORDS):

6. Are the two clusters shown below well separated?

a.Yes

b. No

ANSWER (JUST INDICATE THE LETTER OF YOUR RESPONSE – DO NOT USE WORDS):

7. Explain your answer to item #6.

ANSWER:

8. Using a maximum of 20 words for each response, explain why how anomaly detection is vital in each of the following instances.

a.Intrusion Detection Systems

ANSWER (20 words or less):

b. Fraud Detection in Transactions

ANSWER (20 words or less):

c. Electronic Sensor Events

ANSWER (20 words or less):