Memory Buffered File / Returning summary of a linear model from R-Script to RapidMiner

MPB_
MPB_ New Altair Community Member
edited November 5 in Community Q&A
Hi there,

I am trying to load / read the results of a R-Script in Rapidminer.

As a result of the code:


lm_mod_dyn <- lm(UNITS ~ PR ,data = data)

summary (lm_mod_dyn) 

RapidMiner gives back 
Memory buffered file

In this post it is said, that it is important to convert the results of a script to a dataframe, so I changed the script to:


{


lm_mod_dyn <- lm(UNITS ~ PR ,data = data)


NewData <- data.frame(summary (lm_mod_dyn) )

return(NewData)

}


Now I get a new Error :



Is there a solution for that?


Best regards and have a nice weekend


Best Answer

  • YYH
    YYH
    Altair Employee
    Answer ✓
    Hi @MPB_,

    The function summary.lm computes and returns a list of summary statistics of the fitted linear model. How can we write a list to a data frame? You can use print(summary(model)) in R scripts and the summary will show in your "Log" view.

    Another option is to add some "write" scripts in R like this https://stackoverflow.com/questions/30371516/how-to-save-summarylm-to-a-file/30371944

    If you use GLM model or Logistic Regression in RapidMiner, you can extract the coefficients into a table by "Converters" extension.

    Cheers,

    YY

Answers

  • YYH
    YYH
    Altair Employee
    Answer ✓
    Hi @MPB_,

    The function summary.lm computes and returns a list of summary statistics of the fitted linear model. How can we write a list to a data frame? You can use print(summary(model)) in R scripts and the summary will show in your "Log" view.

    Another option is to add some "write" scripts in R like this https://stackoverflow.com/questions/30371516/how-to-save-summarylm-to-a-file/30371944

    If you use GLM model or Logistic Regression in RapidMiner, you can extract the coefficients into a table by "Converters" extension.

    Cheers,

    YY
  • MPB_
    MPB_ New Altair Community Member
    Hi @yyhuang

    thank you so much for saving me (again).

    Have a great week :)