- What are the characteristics of data?
- Compare the difference in each of the following clustering types: prototype-based, density-based, graph-based.
- What is a scalable clustering algorithm?
- How do you choose the right algorithm?
- What are the characteristics of anomaly detection?
- What are the detection problems and methods?
- What are the statistical approaches when there is an anomaly found?
- Compare and contrast proximity and clustering based approaches
We’ve come to the end of the semester, so now
We’ve come to the end of the semester, so now it’s time to reflect on your experience in HUM 3460. What are your final thoughts? While you do not need to answer all of the questions below, use them to help focus your thinking: Of the topics covered this