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Data mining-Clustering-1

Total questions: 7

Worksheet time: 5mins

Name
Class
Date
1.

Cluster analysis is ...................

a)

Unsupervised Learning

b)

Supervised learning

c)

Semi supervised learning

d)

None of these

2.

Of the following identify the problems that can be solved by cluster analysis

a)

Outlier Detection

b)

Community detection in social network

c)

Sales forecasting

d)

Customer segmentation

3.

Of the following what are the distance based clustering algorithms?

a)

K-Means

b)

K-Medoids

c)

Hierarchical

d)

DBSCAN

4.

K-Means clustering is ........................ type clustering algorithm?

a)

Distance based

b)

Partition based

c)

Density based

d)

Hierarchical

5.

Of the following what are the Density based clustering algorithms?

a)

DBSCAN

b)

OPTICS

c)

BIRCH

d)

CURE

6.

Weblog data is __________________

a)

Time series data

b)

Sequence data

c)

Streaming data

d)

Categorical data

7.

Which of the following statements are true?

a)

Time series data can be sequence data but sequence data need not be Time series data

b)

A Good clustering method will have high intra-class similarity and low inter-class similarity

c)

Similarity measure is critical for cluster analysis

d)

Biological sequence is a Time series data