Naive Bayes Predictor

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 Predictor
Predicts the class per row based on the learned model. The class probability is the product of the probability per attribute and the probability of the class attribute itself.

The probability for nominal values is the number of occurrences of the class value with the given value divided by the number of total occurrences of the class value. The probability of numerical values is calculated by assuming a normal distribution per attribute.

Options

Change prediction column name
When set, you can change the name of the prediction column.(The default is: Prediction (trainingColumn).)
Append columns with normalized class distribution
If selected a column is appended for each class instance with the normalized probability of this row being member of this class.
Suffix for probability columns
Suffix for the normalized distribution columns. Their names are like: P (trainingColumn=value).

Input Ports

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A previously learned naive Bayes model
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Input data to classify

Output Ports

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The input table with one column added containing the classification and the probabilities depending on the options.

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