Indentifying and eliminating insignificant attributes

RepletionRepletion Member Posts: 24 Contributor I
Within statistics we usually operate with a 5% significance value for determining which attributes are significant or insignificant in the model. Thereby one can remove insignificant attributes and get a "simpler" model. How would one go ahead doing this in Rapidminer and is there an automated process for it?


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    lionelderkrikorlionelderkrikor Moderator, RapidMiner Certified Analyst, Member Posts: 1,195 Unicorn
    Hi @Repletion,

    I'm not aware of an implementation of the feature your describe in RapidMiner.
    But more generally, what you describe - get a "simpler" model - is called feature selection.

    In RapidMiner you can apply feature selection by : 
     - Enabling Automatic Feature Selection and choosing your option (simple/balanced/accurate) in Auto-Model.
     - Using directly in your process the Automatic Feature Engineering operator.
     - Using the feature weights operator(s) (Weight by Information GainWeight by Correlation etc.) associated with the Select by Weights operator.

    Hope this helps,



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