data mining

Closed Posted Sep 10, 2015 Paid on delivery
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This document outlines the term paper guidelines for CPS 685. Please read this carefully, as it contains important milestones which must be submitted on BlackBoard by the specified dates. Please contact me if you have any questions or need any assistance

•Sept. 16, 2015: 1-2 page write-up summarizing the topic for your term paper. Topics may range from doing a literature review of an emerging topic in data mining, one or more case studies or applications of data mining, or examining security, privacy and societal impacts of data mining on society. outline(15 Pts)

•Dec. 2, 2015: 6-8 page paper of the literature review. Be prepared to give a 1-2 minutes synopsis of your literature review to the class during the final week of classes. (85 Pts)

Page 2: Table of Contents (Include Title and Section and subsection headings and show page number) {keep single line spacing}

Page 3 – Page n: [Use Palatino / Times Roman /New York -12 point fonts] Title of the Term Paper Summary or Abstract One or two paragraph summary to be included.

I. Introduction. II - ? Body of the term paper

Number each section sequentially. Make sure that text that is extracted from external sources are enclosed in quotation marks, and proper reference is included. Include figures/graphs/tables/ examples liberally. Make sure that identify the source in the captions for figures/graphs/tables/examples by giving proper reference. Do not include any of the abovementioned items without proper caption. [4-5 pages [from Introduction to end of body] is considered adequate]

Last sections: Final Remarks/ Conclusions

a must for the term paper – must be written in your own words – one page per member.

Include your opinions/ predictions/ criticisms/comments

References [use any standard journal format for listing references]

Data Mining

Project ID: #8445880

About the project

2 proposals Remote project Active Nov 3, 2015

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vickkey7

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suyashdhoot

Hi i am a very experienced statistician and writer. I have expertise in data mining and application of data mining techniques in various fields like medicine and finance. Looking forward to discussion, Best Regards More

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