1. What is an attribute and note its importance?
2. What are the different types of attributes?
3. What is the difference between discrete and continuous data?
4. Why is data quality important?
5. What occurs in data preprocessing?
6. In section 2.4, review the measures of similarity and dissimilarity, select one topic and note the key factors.
7. Note the basic concepts in data classification.
8. Discuss the general framework for classification.
9. What is a decision tree and decision tree modifier? Note the importance.
10. What is a hyper-parameter?
11. Note the pitfalls of model selection and evaluation.