Spark Naive Bayes Learner (MLlib)

This node applies the Apache Spark Naive Bayes algorithm. It outputs the original data and the Naive Bayes predictions for the result preview as well as the learned model for later application.

Please note that all data must be numeric, including the label column. Use the Spark Category To Number nodes to convert nominal values to numeric columns. The mapping dictionary of the converter node is the input of second in port of this node.

Use the Spark Predictor node to apply the learned model to unseen data.

Options

Lambda: Additive smoothing parameter between 0 and 1.
Feature Columns: The feature columns to learn the model from. Supports only numeric columns.
Class column: The classification column. Must be numeric.

Input Ports

: Input Spark DataFrame/RDD

Output Ports

: Spark MLlib Naive Bayes Model

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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:

v5.3

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

Plugin provider: KNIME AG, Zurich, Switzerland

Plugin version: 5.3.0.v202406141453

On NodePit since: 2024-07-09

Last update: 2024-11-21

KNIME versions: Since v4.0

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