The node creates a Bayesian model from the given training data. It calculates the number of rows per attribute value per class for nominal attributes and the Gaussian distribution for numerical attributes. The created model could be used in the naive Bayes predictor to predict the class membership of unclassified data. The node displays a warning message if any columns are ignored due to unsupported data types. For example Bit Vector columns are ignored when the PMML compatibility flag is enabled since they are not supported by the PMML standard.
Even if this option is not selected the node creates a valid PMML model. However the model contains KNIME specific information to store missing value and bit vector information. This information is used in the KNIME Naive Bayes Predictor to improve the prediction result but ignored by any other PMML compatible predictor which might result in different prediction results.
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