DAT 220 Fundamentals of Data Mining Milestone 3.docx - Running Head MILESTONE THREE DAT 220 Fundamentals of Data Mining Milestone Three Johnathan James

DAT 220 Fundamentals of Data Mining Milestone 3.docx -...

This preview shows page 1 - 3 out of 3 pages.

Running Head: MILESTONE THREE DAT 220 Fundamentals of Data Mining: Milestone Three Johnathan James April 13, 2019
Image of page 1
Running Head: MILESTONE THREE Milestone Three Analysis Organization Used to segment the customer population into distinct groups with similar attributes was cluster analysis; which utilized the following attributes: age, spend rate, martial-status, and income. Doing so allows for creation of ad campaigns however, by using only one variable (for customers) segments customers. Realizing this, I would use analysis techniques which use more than one variable. Sources of Error Some sources of error were those instances when customers value for web spending did not correlate with customer value for web purchase. To correct this, I chose to remove the data from the set. There was also incorrect data with the JMP data set. Yes No data was set at ordinal data, limiting the data usability. By changing the column modeling type to nominal, I was able to correct the issue.
Image of page 2
Image of page 3

You've reached the end of your free preview.

Want to read all 3 pages?

  • Fall '19

  • Left Quote Icon

    Student Picture

  • Left Quote Icon

    Student Picture

  • Left Quote Icon

    Student Picture