PNN Predictor
The first port contains the PNN 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.
Dialog Options
- 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).
Ports
Input Ports
0 |
PNN Model to which test data is applied.
|
1 |
Test data matching the PNN 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.