Naive Bayes Learner

This Node Is Deprecated — This version of the node has been replaced with a new and improved version. The old version is kept for backwards-compatibility, but for all new workflows we suggest to use the version linked below.
Go to Suggested ReplacementNaive Bayes Learner

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.


Classification Column
The class value column.
Skip missing values (incl. class column)
The node ignores missing values in the model if this option is ticked. If it's not ticked the node treats the missing values as a normal value and considers them during the class probability calculation.
Maximum number of unique nominal values per attribute
All nominal columns with more unique values than the defined number will be skipped during learning. If the column contains missing values and the 'Skip missing values' option is not skipped the missing value counts as one value!

Input Ports

Training data

Output Ports

Learned naive Bayes model

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Naive Bayes Learner View
The view displays the learned model with the number of rows per class attribute. The number of rows per attribute per class for nominal attributes and the Gaussian distribution per class for numerical attributes.




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