My PMML KXEN exported model has problems, how do I fix it?

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The latest KXEN software exports perfect PMML, however if you are using older versions of KXEN, the PMML model it exports may have some problems which will be picked-up by the PMML Converter during conversion or ADAPA during model upload. These hic-ups can be easily fixed. Here is a list of issues we encountered (and remedies we suggest).

1) Your PMML model needs to contain the URL with the address of the PMML schema. Our PMML Converter will add that to the model automatically once you pass it through the converter.

2) Models may contain DerivedFields for which optype = “continuous” but dataType = “string”. Just change the dataType to “double”.

3) Models may contain DerivedFields in which the output of a NormContinuous transformation is a float (dataType = “float”). Change the dataType to “double”.

4) For clustering models, make sure compareFunction = “absdiff” is expressed with a small “d”. Models may refer to “absDiff” instead which is not valid.

5) Again, for clustering models only, delete the element CenterFields (this is not valid PMML).

6) If you have a Mining Model, also check our blog on how to upload KXEN Mining Models into ADAPA.

Your model should be perfect now and ready for


The latest KXEN software exports perfect PMML, however if you are using older versions of KXEN, the PMML model it exports may have some problems which will be picked-up by the PMML Converter during conversion or ADAPA during model upload. These hic-ups can be easily fixed. Here is a list of issues we encountered (and remedies we suggest).

1) Your PMML model needs to contain the URL with the address of the PMML schema. Our PMML Converter will add that to the model automatically once you pass it through the converter.

2) Models may contain DerivedFields for which optype = “continuous” but dataType = “string”. Just change the dataType to “double”.

3) Models may contain DerivedFields in which the output of a NormContinuous transformation is a float (dataType = “float”). Change the dataType to “double”.

4) For clustering models, make sure compareFunction = “absdiff” is expressed with a small “d”. Models may refer to “absDiff” instead which is not valid.

5) Again, for clustering models only, delete the element CenterFields (this is not valid PMML).

6) If you have a Mining Model, also check our blog on how to upload KXEN Mining Models into ADAPA.

Your model should be perfect now and ready for uploading into ADAPA.

Comprehensive blog featuring topics related to predictive analytics with an emphasis on open standards, Predictive Model Markup Language (PMML), cloud computing, as well as the deployment and integration of predictive models in any business process.

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