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Answer your choice of one of the discussion questions below. Please note that you can only address a question that has not yet been answered by a classmate. If all questions have already been answered, then you are free to select any question. Please clearly indicate which question you’re answering by labeling it with the question number (e.g. “Question 1”).
1. Define the data mining technique of cluster analysis, and describe the various clustering methods.
2. Define the data mining technique of classification, and describe the various classification techniques.
3. Define the data mining technique of association rule mining, and give an example of how it would be used.
4. What is the lift value in an association rule?
5. What two numbers are used to express the degree of uncertainty about a rule identified in association rule mining? Define each.
6. Define the data mining technique of cause-and-effect modeling, and give an example of how it would be used.
7. Define lagging and leading measures in cause-and-effect modeling, and give an example of each.
8. Explain logistic regression for classifying data, and discuss how it is different from linear regression.
Your initial post must be at least 200 words in length and must reference the text. Each subsequent post must be at least 100 words in length. All posts need to add significant value to the discussion. Each post you make needs to pertain to a different question (e.g. if your primary response was to Question 1, then none of your subsequent responses should pertain to Question 1). Avoid late Sunday evening posts. You must cite all sources (references and corresponding in-text citations). Make sure to adhere to all other aspects that I’ve outlined in my guidelines announcement.