Sklearn Classification Predictor (Labs)

The Classification Predictor Node accepts a trained model from any of the classification learner nodes and computes the predicted class for each row of the given input table. Optionally, class probability estimates for each row can also be predicted.

It is only executable if the test data contains the columns that are used by the learner model.

Options

Output

Custom prediction column name: If no name is specified for the prediction column, it will default to <target_column_name>_pred.
Predict probability estimates: Predict probability estimates for each target class.
Suffix for probability columns: Allows to add a suffix for the class probability columns.

Input Ports

: Trained classification predictor model.
: All feature columns used for training must also be present in the table for prediction.

Output Ports

: The input table concatenated with a predictions column and optionally class probabilities.

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Installation

To use this node in KNIME, install the extension KNIME Python Extension Development (Labs) from the below update site following our NodePit Product and Node Installation Guide:

v5.4

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

Plugin provider: KNIME AG, Zurich, Switzerland

Plugin version: 5.4.0.v202411281010

On NodePit since: 2024-12-06

Last update: 2024-12-21

KNIME versions: Since v5.2

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