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Text Analytics - Is there a way to have one to many words correlation in RapidMiner?

svtorykhsvtorykh Member Posts: 35  Guru
edited November 10 in Help

Hi RM support! I know how to have one-to-one word correlations with Correlation Matrix. Is there a way to have words correlated in one to many relationship? For example in my text I can see that Amazon is correlated with Prime. I also know that in the text Amazon, Prime and Shipping are also interchangibly correlated. So how I can show all 3 of them being correlated using RapidMiner?
Thanks much!

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Best Answer

  • svtorykhsvtorykh Posts: 35  Guru
    Solution Accepted

    Hi Scott,

     

    So I have rerun my data through Association Rules. What is the definition of Premises and Conclusion? Couldn't find it in operator description.

    Thanks much!

Answers

  • sgenzersgenzer Administrator, Moderator, Employee, RapidMiner Certified Analyst, Community Manager Posts: 1,892  Community Manager

    hello @svtorykh - welcome to the community. Seems more like an association mining problem than correlation. Have you tried that approach?

     

    Scott

     

  • svtorykhsvtorykh Member Posts: 35  Guru

    Hi Scott! Thanks for your reply. Is it the process utilizing Fp-Growth? I think I have that but results are difficult to interpret in terms of rules generated.

  • sgenzersgenzer Administrator, Moderator, Employee, RapidMiner Certified Analyst, Community Manager Posts: 1,892  Community Manager

    yes exactly. I'd recommend going through a tutorial. Have you looked at the Market Basket Analysis Template?

     

    Screen Shot 2018-01-11 at 11.49.37 AM.png

     

    Scott

     

     

  • lionelderkrikorlionelderkrikor Moderator, RapidMiner Certified Analyst, Member Posts: 564   Unicorn

    Hi @svtorykh

     

    Here a description of Premises and Conclusion : 

    Association_rules_1.png

     

    Association_rules_1_b.png

     

    Regards, 

     

    Lionel

     

     

     

    sgenzerThomas_Ott
  • svtorykhsvtorykh Member Posts: 35  Guru

    Thank you!

    sgenzer
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