The following node is available in the Open Source KNIME predictive analytics and data mining platform version 2.7.1. Discover over 1000 other nodes, as well as enterprise functionality at http://knime.com.

Fuzzy Rule Predictor

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

Dialog Options

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.

Ports

Input Ports
0 Fuzzy Rule Model to which test data is applied.
1 Test data matching the Fuzzy Rule Model structure.
Output Ports
0 Predicted data with one additional classification column.
This node is contained in KNIME Base Nodes provided by KNIME GmbH, Konstanz, Germany.