Order ID:89JHGSJE83839 | Style:APA/MLA/Harvard/Chicago | Pages:5-10 |
Instructions:
Using Weka as a Machine Learning Classifier
Upload the final data file in the first section.
Section 2: Questions about business or research
1. State the three business or research questions that you have attempted to answer through your analysis using the BRFSS data set, and explain why they are interesting (300 words maximum)
Section 3 Data Processing
1. Describe how you looked at the data, why you did so, and what conclusions you came to (300 words maximum)
2. Describe the data cleaning/fixing you did and why (300 words)
DATA ANALYSIS (Section 4)
3. Why did you use the analysis techniques you did to answer your business/research questions? (300 words maximum)
4. Summarize the findings of your investigation (300 words maximum)
5. What do the findings reveal in response to your business/research inquiries? (maximum of 300 words)
6. Describe the most serious threats to validity that you found in your investigation (300 words maximum)
Dealing with Large Data Sets (Section 5)
7. Describe how you would represent the data in a relational database, including a schema and a mechanism for converting it to a WEKA-compatible input form (300 words maximum)
8. Describe how you could use appropriate technologies to distribute the load across multiple computers, and why you think this is a good idea (300 words maximum)
Privacy (section 6)
9. List the three most important privacy concerns raised by this analysis, along with strategies for dealing with each (300 words maximum)
Report references (section 7)
10. Provide a properly formatted reference list for all of the resources used in this development and report (no word limit)
RUBRIC |
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Excellent Quality 95-100%
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Introduction
45-41 points The background and significance of the problem and a clear statement of the research purpose is provided. The search history is mentioned. |
Literature Support 91-84 points The background and significance of the problem and a clear statement of the research purpose is provided. The search history is mentioned. |
Methodology 58-53 points Content is well-organized with headings for each slide and bulleted lists to group related material as needed. Use of font, color, graphics, effects, etc. to enhance readability and presentation content is excellent. Length requirements of 10 slides/pages or less is met. |
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Average Score 50-85% |
40-38 points More depth/detail for the background and significance is needed, or the research detail is not clear. No search history information is provided. |
83-76 points Review of relevant theoretical literature is evident, but there is little integration of studies into concepts related to problem. Review is partially focused and organized. Supporting and opposing research are included. Summary of information presented is included. Conclusion may not contain a biblical integration. |
52-49 points Content is somewhat organized, but no structure is apparent. The use of font, color, graphics, effects, etc. is occasionally detracting to the presentation content. Length requirements may not be met. |
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Poor Quality 0-45% |
37-1 points The background and/or significance are missing. No search history information is provided. |
75-1 points Review of relevant theoretical literature is evident, but there is no integration of studies into concepts related to problem. Review is partially focused and organized. Supporting and opposing research are not included in the summary of information presented. Conclusion does not contain a biblical integration. |
48-1 points There is no clear or logical organizational structure. No logical sequence is apparent. The use of font, color, graphics, effects etc. is often detracting to the presentation content. Length requirements may not be met |
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Using Weka as a Machine Learning Classifier |
Using Weka as a Machine Learning Classifier