Finding an incorrect grading pattern

marketa_vackovamarketa_vackova Member Posts: 2 Contributor I
edited November 2018 in Help

I was given a labelled data set and I was told few of the labels are wrongly assigned, i.e. some of the data were graded inaccurately. I'm supposed to find which ones. Which tool in RapidMiner should I use?

I tried the operator Find Outliers (Density), but somehow I feel that is not the one I'm looking for.

Thank you very much for advice. Markéta


  • IngoRMIngoRM Administrator, Moderator, Employee, RapidMiner Certified Analyst, RapidMiner Certified Expert, Community Manager, RMResearcher, Member, University Professor Posts: 1,729  RM Founder

    Here is an idea: you could train a model on the data set which is generalizing well (no overfitting, no k-nn with 1 neighbor only, you get the idea...) and then apply this model to the training data set again.  Whenever the prediction differs from the label, this could be a good candidate for wrongly labeled.


    Just my 2c,


  • Telcontar120Telcontar120 Moderator, RapidMiner Certified Analyst, RapidMiner Certified Expert, Member Posts: 1,308   Unicorn

    Another potenial approach would be to run a clustering analysis on the labeled classes separately and then look for individual outliers that way.  



    Brian T.
    Lindon Ventures 
    Data Science Consulting from Certified RapidMiner Experts
Sign In or Register to comment.