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Get TSmodel nugget's results using Python on SPSS Modeler 18.x or higher versions

When generating a nugget from a Temporal Series model, we need to get model metadata from Python code.

For example, if the TS Model is configured to indicate the technique automatically using the Expert Modeler Parameter after the Nugget generation, we need to store the recommended model and sub-model. For this, we use the following Python commands in SPSS Modeler V17.0:


nugget_outs = nugget_model.model.modelStatisticsStrings [0] .split (',')
nugget_outs = nugget_outs [1] .split ('-')
nugget_metodo = int (nugget_outs [0])

We need this feature to be available again. This feature is very important to keep metadata about our projections and our internal controllers.

Note: We've Support Reference about this: PMR: 66638,999,631 - https://www-947.ibm.com/support/servicerequest/problemDescriptionSelect.action?srNumber=66638&branch=999&retainCountryCode=631&sourceAppl=XSR&sourceNode=prNode2&sourceTranId=85851528724057107&draft=0

  • Guest
  • Jul 2 2018
  • Needs review
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