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030001T304052001

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Mention the issues regarding classification and prediction.
PART C
Answer any two full questions, each carries 20 marks.
Write note on CRM data mining models.

Draw the classification framework for data mining techniques in CRM and
explain in detail.

Explain the different stages of Customer life cycle with a neat diagram?
Given two objects represented by the tuples (22, 1, 42, 10) and (20, 0, 36, 8)
i) Compute the Eucleidian distance between the two objects.

ii) Compute the Manhattan distance between the two objects.

Use K-means clustering algorithm to divide the following data into two
clusters and also compute the representative data points for the clusters

assuming the initial cluster centre as (2,1) and (2,3).
| 1 | 2 (ख
೫2 | 1 | | 1 | 3

Mention any four features of R programming.

Differentiate web content mining and web structure mining.

Write an algorithm for k-nearest neighbour classification given k and n, the
number of attributes describing each tuple.

How density based clustering varies from other methods?

List the advantages and disadvantages of K-means clustering.

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