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SmartData Collective > Uncategorized > How does ADAPA handle missing values for Decision Trees?
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How does ADAPA handle missing values for Decision Trees?

MichaelZeller
Last updated: 2009/04/22 at 11:26 AM
MichaelZeller
1 Min Read
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PMML 3.2 offers many different strategies for the handling of missing values in Decision Trees. ADAPA supports all of them. These are:

  • lastPrediction
  • nullPrediction
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  • defaultChild
  • weightedConfidence
  • aggregateNodes
  • none (default strategy)

For information on each strategy, please visit the PMML 3.2 Decision Trees specification page at the Data Mining Group website.


PMML 3.2 offers many different strategies for the handling of missing values in Decision Trees. ADAPA supports all of them. These are:

  • lastPrediction
  • nullPrediction
  • defaultChild
  • weightedConfidence
  • aggregateNodes
  • none (default strategy)

For information on each strategy, please visit the PMML 3.2 Decision Trees specification page at the Data Mining Group website.

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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MichaelZeller April 22, 2009
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