in the performance(Classification) operator, correlation is defined as correlation between the label and the prediction, but how is this calculated? with which informaion criteria? I dont understand the results...
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MartinLiebigAdministrator, Moderator, Employee, RapidMiner Certified Analyst, RapidMiner Certified Expert, University ProfessorPosts: 3,508 RM Data Scientist
I think its standard pearson correlation with by using the integer mapping of the classes.
~Martin
- Sr. Director Data Solutions, Altair RapidMiner - Dortmund, Germany
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IngoRMAdministrator, Moderator, Employee, RapidMiner Certified Analyst, RapidMiner Certified Expert, Community Manager, RMResearcher, Member, University ProfessorPosts: 1,751 RM Founder
Hi,
Just looked up the Java doc and here is what it says: Computes the empirical corelation coefficient 'r' between label and prediction. For P=prediction, L=label, V=Variance, Cov=Covariance we calculate r by: Cov(L,P) / sqrt(V(L)*V(P))
So it is the Pearson correlation between the label and the prediction. Judging from a quick check of the source code itself this description is accurate.
Unicorn
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I think its standard pearson correlation with by using the integer mapping of the classes.
~Martin
Dortmund, Germany
Hi,
Just looked up the Java doc and here is what it says: Computes the empirical corelation coefficient 'r' between label and prediction. For
P=prediction, L=label, V=Variance, Cov=Covariancewe calculate r by:Cov(L,P) / sqrt(V(L)*V(P))So it is the Pearson correlation between the label and the prediction. Judging from a quick check of the source code itself this description is accurate.Cheers,Ingo