data mining homework

Homework 8

Answer the following questions: (10 point each)

1. Name at least one situation in which you would not want to use clustering based on SNN similarity or density.

2. Explain the difference between likelihood and probability.

3. Discuss the advantages and disadvantages of treating clustering as an optimization problem. Among other factors, consider efficiency, non-determinism, and whether an optimization-based approach captures all types of clusterings that are of interest.

4. Traditional K-means has a number of limitations, such as sensitivity to outliers

and difficulty in handling clusters of different sizes and densities, or with

non-globular shapes. Comment on the ability of fuzzy c-means to handle

these situations.

5. Table 8.1 lists the two nearest neighbors of four points. Calculate the SNN similarity between each pair of points using the definition of SNN similarity defined in Algorithm 8.10. The following is the SNN similarity matrix.

1