Weka Predictor (3.7)

The Weka Predictor takes a model generated in a weka node and classifies the test data at the inport.

Options

Perform evaluation: Whether the Weka evaluation of the classifier model should be performed. If checked, the evaluation summary will be available in the node view. The evaluation is only possible if the class-column used for training is present in the input table. If an evaluation is performed, all data is additionally copied and kept in memory!
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: Shows the normalized class distribution for each prediction.
Suffix for probability columns: Suffix for the normalized distribution columns. Their names are like: P ( trainingColumn = value ) .

Weka Node View: Each Weka node provides a summary view that provides information about the classification. If the test data contains a class column, an evaluation is generated.

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To use this node in KNIME, install the extension KNIME Weka Data Mining Integration (3.7) from the below update site following our NodePit Product and Node Installation Guide:

v5.3

A zipped version of the software site can be downloaded here.

Plugin provider: KNIME AG, Zurich, Switzerland

Plugin version: 5.3.0.v202312081535

On NodePit since: 2024-07-09

Last update: 2024-11-20

KNIME versions: Since v3.6

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