Data Mining

a. Briefly describe why clusteirng is one kind of unsupervised learning

b. Briefly descirbe how a K-means clustering works

c. Briefly describe the main difference between K-means and K-medoid methods.

d. In data mining, one of the fields is outlier analysis. Explain what is an outlier? Are outliers noise data?

e. A good clustering method will produce high quality clusters. What criteria can we use to judge where clusters are high quality clusters?

f. List out at least two drawbacks of K-means clustering approaching. In hierarchical clustering, there are different ways to measure the distances between clusters, e.g. single linkage, complete linkage, and average linkage. Briefly describe the difference among these three distance measures.

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