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data mining.

data mining.

data mining.

 

  • Week 1 DiscussionThis week our focus is on data mining. In the article this week, we focus on deciding whether the results of two different data mining algorithms provides significantly different information.  Therefore, answer the following questions:
    1. When using different data algorithms, why is it fundamentally important to understand why they are being used?
    2. If there are significant differences in the data output, how can this happen and why is it important to note the differences?
    3. Who should determine which algorithm is “right” and the one to keep?  Why?
    4. Requirements: 
    • Students must not copy and post from sources.  When referencing sources, students must rephrase all work from author’s and include in-text citations and references in APA format. 
    • Students must post their initial post by Thursday evening at 11:59 pm ET and have two total days of engagement (the first day of engagement must answer the initial post and then at least one more additional day of engagement with peers).  All posts must be answered by Sunday at 11:59 pm ET. 
    • The initial discussion board posts must be from 100-150 words. 
    • Peer responses must be 50-100 words.  
    • The content must also not be from the textbook. 
    • Peer responses must be substantive in nature. 
      • Build on something your classmate said. 
      • Explain why and how you see things differently. 
      • Ask a probing or clarifying question. 
      • Share an insight from having read your classmate’s posting. 
      • Offer and support an opinion. 
      • Expand on your classmate’s posting. 
    • Peer responses that are “a good job” or “I agree” do not count as substantive post.  
  • AssignmentWeek 1 HomeworkThis week we focus on the introductory chapter in which we review data mining and the key components of data mining.  In below format answer the following questions:
    1. What is knowledge discovery in databases (KDD)? 
    2. Review section 1.2 and review the various motivating challenges.  Select one and note what it is and why it is a challenge.
    3. Note how data mining integrates with the components of statistics and AL, ML, and Pattern Recognition.
    4. Note the difference between predictive and descriptive tasks and the importance of each.
    5. In an APA7 formatted answer all questions above.  There should be headings to each of the questions above as well.  Ensure there are at least two-peer reviewed sources to support your work. The paper should be at least two pages of content (this does not include the cover page or reference page).

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