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.