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Fuzzy Rule Predictor

StreamableKNIME Base Nodes version 4.0.2.v201909251340 by KNIME AG, Zurich, Switzerland

The first port contains the Fuzzy Rule Model that is applied to the test data contained in the second input port. The output data has then one additional column containing the predicted class attribute which is the best match for all rules.


Don't Know Class
Ignore If selected, no lower degree of class activation is set, otherwise the specified value between 0 and 1 is used.
Default Use the minimum activation threshold from the learning algorithm.
Use Instances where the activation lies above this threshold are classified as a missing (unknown) class. This is useful in cases where the feature space is not completely covered by rules.
Change prediction column name
When set, you can change the name of the prediction column.
Prediction Column
The possibly overridden column name for the predicted column. (The default is: Prediction (trainingColumn).)
Append columns with normalized class distribution
Compute the probabilities for the different classes.
Suffix for probability columns
Suffix for the normalized distribution columns. Their names are like: P (trainingColumn=value).

Input Ports

Fuzzy Rule Model to which test data is applied.
Test data matching the Fuzzy Rule Model structure.

Output Ports

Predicted data with one additional classification column.

Best Friends (Incoming)

Best Friends (Outgoing)


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