Spark Predictor (Regression)

This node applies regression to input data using a previously learned Spark ML regression model. Please note that all feature columns selected during model training must be present in the ingoing DataFrame.

Note: This node is not compatible with Spark MLlib models. For these models please use the Spark Predictor node.

This node requires at least Apache Spark 2.0.

Options

Change prediction column name: When set, you can change the name of the prediction column. The default name is "Prediction (targetcolumn)".
Prediction Column: The desired name for the prediction column.

Input Ports

: Spark ML regression model to use.
: Spark DataFrame containing the input data to apply regression on.

Output Ports

: Input DataFrame with appended prediction column.

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Installation

To use this node in KNIME, install the extension KNIME Extension for Apache Spark (legacy) from the below update site following our NodePit Product and Node Installation Guide:

v5.2

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

Plugin provider: KNIME AG, Zurich, Switzerland

Plugin version: 5.2.0.v202311021430

On NodePit since: 2023-12-06

Last update: 2024-04-25

KNIME versions: Since v4.0

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