validation and meta cost
Hello everyone. I am glad that these forums are so newbie friendly. I am able to run a simple decision tree learner and have had success using both cross validation and simple validation. What I would like to do it increase the class recall of the model -- in this case I have two outcomes (students who are at risk and those who are not) and 8 nominal, ordinal, and real attributes derived from a much larger set using logistic regression.
What I would like to do is attach costs to the model -- namely making it more costly to say that a student at risk will be fine -- but when I add the metacost operator and move the DT operator into it RM gives me an error:
Thanks, --chris
What I would like to do is attach costs to the model -- namely making it more costly to say that a student at risk will be fine -- but when I add the metacost operator and move the DT operator into it RM gives me an error:
P Aug 23, 2008 11:32:42 PM: Test: Set parameters for com.rapidminer.operator.learner.meta.MetaCostModelThat snippet is from the log set in verbose mode, so I am wondering if I am just trying to do something invalid, if I have something out of order, or if I just don't know what I am doing.
P Aug 23, 2008 11:32:42 PM: Test: Applying com.rapidminer.operator.learner.meta.MetaCostModel
P Aug 23, 2008 11:32:42 PM: [Fatal] ArrayIndexOutOfBoundsException occured in 1st application of Test (ModelApplier)
P Aug 23, 2008 11:32:42 PM: [Fatal] Process failed: operator cannot be executed. Check the log messages...
Root[1] (Process)
+- ExampleSource[1] (ExampleSource)
+- SimpleValidation[1] (SimpleValidation)
+- MetaCost[1] (MetaCost)
| +- DecisionTree[10] (DecisionTree)
+- ApplierChain[1] (OperatorChain)
here ==> +- Test[1] (ModelApplier)
+- Performance[0] (Performance)
Thanks, --chris