Compare K-means and K-medoids algorithms. List down the main differences between these two algorithms?
Cluster the following eightpoints into three clusters using K means clustering algorithm and use Euclidean distance.
A1=(2,10), A2=(2,5), A3=(8,4), A4=(5,8),
A5=(7,5), A6=(6,4), A7=(1,2), A8=(4,9).
a) Create distance matrix by calculating Euclidean distance between each pair of points. (0.5 mark)
b) Suppose that the initial centers of each cluster are A1, A4 and A7. Run the k-means algorithm for once only and show:
i. The new clusters (i.e. the examples belonging to each cluster) (1 mark)
ii. The centers of the new clusters (0.5 mark)
Show all your work.
Define partitioning clustering approaches and hierarchical clustering approaches and give a typical method for each type. Also state the main difference between these two approaches?
Deadline: Day 07/04/2018 @ 23:59
[Total Mark for this Assignment is 4]
Data Mining & Data Warehousing
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