IndexOutOfBoundsException
tcm5026
New Altair Community Member
Hello,
I am trying to select the ten most "important" variables out of 24. The goal is to use the first component of PCA analysis to find these ten variables. I have set "generations_without_improval" in the WeightGuidedFeatureSelection to 14 - so that ten variables are selection. I've tried various numbers and sometimes I get the following error and sometimes I do not. The error I keep getting is, "Process Failed IndexOutOfBoundException caught: Index:0, Size:0.
My process looks like this,
Root
>ExampleSource
>PCAWeighting
>WeightGuidedFeatureSelection
>>Xvalidation
>>>LinearRegression
>>>OperatorChain
>>>>ModelApplier
>>>>RegressionPerformance
Does anyone know what this error means? I've tried searching the documentation but cannot find it. Does anyone know possibly a different way to use PCA to select the ten most "important" variables (i.e. eliminating the redundant members)? Thanks for any help as it is greatly appreciated!!!
-Tyler
I am trying to select the ten most "important" variables out of 24. The goal is to use the first component of PCA analysis to find these ten variables. I have set "generations_without_improval" in the WeightGuidedFeatureSelection to 14 - so that ten variables are selection. I've tried various numbers and sometimes I get the following error and sometimes I do not. The error I keep getting is, "Process Failed IndexOutOfBoundException caught: Index:0, Size:0.
My process looks like this,
Root
>ExampleSource
>PCAWeighting
>WeightGuidedFeatureSelection
>>Xvalidation
>>>LinearRegression
>>>OperatorChain
>>>>ModelApplier
>>>>RegressionPerformance
Does anyone know what this error means? I've tried searching the documentation but cannot find it. Does anyone know possibly a different way to use PCA to select the ten most "important" variables (i.e. eliminating the redundant members)? Thanks for any help as it is greatly appreciated!!!
-Tyler
Tagged:
0
Answers
-
Hi,
this error message denotes an internal memory addressing issue, that is simply a bug and not a hand crafted error message standing anywhere in the documentation.
I would suggest to update to RapidMiner 5.0, since we don't maintain the RapidMiner 4.6 community version anymore. There's a fair chance this issue has already be solved with RapidMiner 5.
Greetings,
Sebastian0
