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Fuzzy Rule Predictor

DeprecatedKNIME Base Nodes version 4.2.2.v202009011342 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.


Choose Name
The name of the predicted column appended to the end of the test data.
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.

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.


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