Generating Simulated DataFrame

cedric_anovercedric_anover MemberPosts:5Contributor I
edited December 2018 in公关oduct Feedback - Resolved

This is an Operator Idea where it takes a DataSet as input and then it analyze/estimate the distribution of each attributes/columns, and then outputs another dataframe (which may have different nuber of rows) with same columns/attributes but have different simulated observations/examples.

输入:

  • DF(Type: DataFrame)

Parameters:

  • nrow (Type: Int) = nrow of DF (by default)

Output:

  • DF_Out(类型:DataFrame)
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Declined·Last Updated

no comments or votes in over a year - closing this idea for now. Please comment if still relevant.

Comments

  • MartinLiebigMartinLiebig Administrator, Moderator, Employee, RapidMiner Certified Analyst, RapidMiner Certified Expert, University ProfessorPosts:3,404RM Data Scientist

    Dear@cedric_anover,

    what do you mean by "analyze/estimate the distribution"? Simple check for usual distributions like Normal, Poisson or Cauchy?

    I think this is rather academic, because in real life distributions aren't that easy. If you don't use the histogram as a estimate for the pdf you get a problem. In any case, these simulations are not taking account dependecies between two attributes (or more). If you want to do it more correctly you are forced to use techniques like Markov Chain i suppose.

    Best,

    Martin

    - Sr. Director Data Solutions, Altair RapidMiner -
    Dortmund, Germany
  • sgenzersgenzer Administrator, Moderator, Employee, RapidMiner Certified Analyst, Community Manager, Member, University Professor, PM ModeratorPosts:2,959Community Manager

    pending response from user

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