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Slow Performance Issue with Rapid Miner Outlier Detection
shredlegend88
Member Posts: 10 
Contributor II
I have a recordset of just over 10,000 records with 8 columns and I tried using the outlier detection operator and it is taking a very long time to run. I have tried the different outlier detection methods (LOF, COF, etc.) and tried different number of neighbors and other optional tweaks. I tried allocating more RAM to the Java process, set the java process to high priority, but nothing seems to have an impact. I wouldn't think it would take so much for such a small dataset. I have the educational licensed version if that helps.
If anyone has suggestions on improving the performane of this particular operator, much would be appreciated.
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Answers
Hey,
did you use the outlier extension and where dates included?
~Martin
Dortmund, Germany
I am not sure if the base studio product came with extensions included, but I just used the Outlier Detection operator and no dates were involved, mostly dummy variables and a few continuous variables.
I just let it run, and it took about 10 minutes or so. Which is fine if I walk away from it, I just thought it was weird to be so slow for such a small dataset for an enterprise data mining product.