Naive Bayes
A PMML Naive Bayes model predicts the value of a target from evidence given by one or more predictor fields using Bayes' Theorem. Naive Bayes models require the target field to be discretized so that a finite number of values are considered by the model. Predictor fields may be either discrete or continuous.
Model Element
<NaiveBayesModel functionName="classification" ...Unsupported Features
Naive Bayes models with the <MiningSchema> element containing a reference to a <DerivedField> element are not supported.
Model Outputs
By default the target field will be available as an output field - this is a synonym for the predictedValue feature.
| Supported Model Output Features | Description |
|---|---|
|
predictedValue |
The categorical variable that we are predicting membership of. |
|
transformedValue |
A value generated via a transformation expression applied to the predicted model output. |
|
decision |
A value generated via an expression applied to the predicted model output resulting in a categorized value. |
|
predictedDisplayValue |
The human readable value used to represent the predicted value from the model. |
|
probability |
The statistical probability of the predicted value. |
|
residual |
The residual of the probability output value (1 - probability) for the predicted value. |