Machine Learning Classifier using Weka

Section 1 — Upload final data file
Section 2 — Business/research questions
1. Using BRFSS data set, state the three business or research questions that you have attempted to answer through your analysis, and justify why they are interesting (300 words maximum)
Section 3 — Processing the data
1. Describe how you explored the data, why you did it that way, and what conclusions you drew about it (300 words maximum)
2. Describe the cleaning/fixing you did on the data, and why (300 words)
Section 4 — Data analysis
3. Explain what analysis techniques you used to answer your business/research questions, and why (300 words maximum)
4. Summarise the results of your analysis (300 words maximum)
5. What do the results say in answer to your business/research questions? (300 words maximum)
6. Describe the most salient threats to validity that remain in your analysis (300 words maximum)
Section 5 — Dealing with large data sets
7. Describe how you could represent the data in a relational database — give a suitable schema, and describe a mechanism for converting it to a suitable input form for WEKA (300 words maximum)
8. Describe a way that you could use appropriate technologies to spread the load over multiple computers, and justify why this would be a good approach (300 words maximum)
Section 6 — Privacy
9. List the three most salient privacy issues related to this analysis, and give strategies you could use to address each of them (300 words maximum)
Section 7 — Report references
10. Provide a correctly structured list of references to all the resources used for this development and report (no word limit)