Wednesday, April 16, 2008

ADAPA's computed value is not the same as the expected value, why is that?

There are many reasons for the validation test to fail. I can think of two main reasons.

1) The model ADAPA loaded and executed may be different than the model you built in your development environment. This may reflect a problem with ADAPA or see below.

2) It may be the case that the PMML file you got out of your model development environment does not really represent all aspects of the model or is problematic semantically speaking.

In both cases, you can try to follow ADAPA's decisions by clicking on the row id for the record you want to look at in the ADAPA Console (see figure below - orange arrow points to row id 3). The row id is a hyperlink and will allow you to download a text file containing a log of computations. This may be very helpful in determining why ADAPA generated the value(s) it did.


Also, the problem may have to do with your data validation file itself. It may be the case that you generated your model in SPSS, for example, exported it as a PMML file and uploaded it into ADAPA. So far so good, but how about the data? If you saved your data in SPSS as well, you have to make sure you saved the expected value or prediction with the correct name. SPSS usually calls this value "PRE_1." You will need to change the name of this variable to the name of the predicted variable defined in the PMML file. Also, if your data contains the original target used to build the model, you will need to rename it to something different than the predicted variable. Your new predicted variable now should be the predicted result you got out of SPSS or any model development environment you used to score the data in the first place.

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