Association Rules

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School

Grand Canyon University *

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455

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Computer Science

Date

Oct 30, 2023

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docx

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2

Uploaded by PrivateFlower5518

John Burciaga Kellermann BIT-445: Data Mining Professor Perkins 10/22/2023 Association Rules: Montana Economic Status I started off by looking over the “Polls” data set to ensure everything with the data looked normal. Something I noticed immediately was that several data cells were marked with an *. This meant that data was not reported for that specific cell. After noticing this, I made sure I removed all subjects that were missing any type of data from the Excel sheet. Once I had ensured that the data looked right, I ran an analysis of the data in Knime, leaving me with a series of association rules. Only four of them made sense and were applicable. One error I noticed on the website was that the author of the excel file had STAT1 listed as people who thought the financial state was better off than the year before, and STAT2 as people who thought it was worse off than the year before. This was wrong, as in the Excel file there was only STAT0 and STAT1. Given this, I assumed that STAT0 had the same meaning as STAT1 in the authors write up, and STAT1 was aligned with STAT2. Association Rules: All of the following believe state economic outlook is better now than it was one year ago. 1. Subjects from Northeastern region. ( Lift : 1.206) 2. Subjects who had a worse financial status last year. ( Lift : 1.174) 3. Subjects who are between the ages of 35 to 54 years old. ( Lift : 1.111) 4. Subjects who were females. ( Lift : 1.111) After discovering these rules, I had to interpret them and decide what they meant. Starting with the subjects from the Northeastern region of Montana; These people live in areas with a far lower cost of living and lower population than the other two areas. They deal with less big city issues as well. Given this information, it would make sense that most of the people from Northeastern Montana would view the state as being in a better economic space. It makes sense that people who are now in a better personal financial spot would also have a more positive outlook on economics all around, therefore, making rule #2 valid. Those who are between the age of 35 years old and 54 years old tend to have better paying jobs than those of the other age brackets and have a good grasp of current political and economic status of their local areas, which would justify this association rule. I believe this data could have been more accurate had they enforced that subjects provided answers to all of the fields. None of the questions were too difficult to understand or formulate an opinion on. Some of them were even easier to answer, as they only had to reveal 1 of 3 regions they lived in, their age, and their gender. Aside from this, the data collection had enough information to make accurate association rules, as they were all understandable and justifiable with logic.
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