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Operators to split data into multiple tables etc

aldavenportaldavenport Member Posts: 2 Newbie
edited June 14 in Help
Hello,
I am working on a college project of which involves taking a CSV file and breaking the data by class into different tables. My goal is to then run a probability assessment against these tables and hopefully output a percentage. I am new to RapidMiner and am having some issues with the operators. Does anyone here have any helpful tips? Anything would be greatly appreciated.
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Answers

  • rfuentealbarfuentealba Moderator, RapidMiner Certified Analyst, Member, University Professor Posts: 417   Unicorn
    Hello @aldavenport,

    If your CSV has something like:

    id,att1,att2,class
    0,0,0,none
    1,1,1,odd
    2,2,1,even
    3,3,2,odd
    4,4,3,even
    5,5,5,odd
    6,6,8,even

    There are many ways to do this. The simple one would be a chain of "Filter Examples" plus "Store". You Read CSV and then apply as many Filter Examples operators as classes you have, and then store these (wherever you want)



    A more complex one would be this:



    This one multiplies the data from the CSV. First line (on the top) it selects and removes the duplicates of your data, and then it loops over each information related with the class.

    (Make sure this is the order you have at this level)


    Inside the Loop Examples operator, you can have this:



    That uses the Extract Macro operator to filter the examples recalled and store these, no matter how many classes you have.

    Hope this helps,

    Rodrigo.
    aldavenportvarunm1sgenzer
  • aldavenportaldavenport Member Posts: 2 Newbie
    Thank you Rodrigo! I am going to give these examples a shot. Again, thank you!
    rfuentealba
  • mschmitzmschmitz Administrator, Moderator, Employee, RapidMiner Certified Analyst, RapidMiner Certified Expert, University Professor Posts: 2,154  RM Data Scientist
    Another nice option is the Group Into Collection operator from Operator Toolbox.

    Best,
    Martin
    - Head of Data Science Services at RapidMiner -
    Dortmund, Germany
    varunm1aldavenportrfuentealba
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