Computer Science Homework Help

Week 10 Discussion

1. What is K-means from a basic standpoint?
2. What are the various types of clusters and why is the      distinction important?
3. What are the strengths and weaknesses of K-means?
4. What is a cluster evaluation?

Select at least two types of cluster evaluations, discuss the concepts of each method.

Should return Main Discussion      Content in 15hrs.

• once I receive the main      discussion content then I will post the peer discussion in chat
• peer response should be      returned in next 10hrs.

Week 10 Homework

After reviewing the case study this week by Krizanic (2020), answer the following questions in essay format.

1. What is the definition of data mining that the author      mentions?  How is this different from our current understanding of      data mining?
2. What is the premise of the use case and findings?
3. What type of tools are used in the data mining aspect      of the use case and how are they used?
4. Were the tools used appropriate for the use case?       Why or why not?

Week 11 Discussion

In chapter 8 we focus on cluster analysis.  Therefore, after reading the chapter answer the following questions:

1. What are the characteristics of data?
2. Compare the difference in each of the following      clustering types: prototype-based, density-based, graph-based.
3. What is a scalable clustering algorithm?
4. How do you choose the right algorithm?