How does ADAPA handle missing values for Decision Trees?
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.
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.
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