Exam

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1. What is Data Exploration?

2. Describe the four Basic Decision Tree Learning Methods?

3. Describe the two main Characteristics of Rule-Based Classifier.

4. Suppose that there’s a total of 50 data mining related documents in a library of 200 documents.  Suppose that a search engine retrieves 10 documents after a user enters ‘data mining’ as a query, of which 5 are data mining related documents.  What are the precision and recall?

5. There are 7 common challenges of Data Mining. List the challenges below:

6. What is the Two-Step approach of Mining Association Rules?

7. What are the 4 types of Attributes in Data Mining? Provide an example of each type of Attributes:

  

8. Describe and Explain the   differences between Discrete and Continuous Attributes:

 

9. List and Explain the three   “Frequent Itemset Generation Strategies”:

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