Spark Normalizer

This node normalizes the values of all selected (numeric) columns.

Options

Min-max normalization: Linear transformation of all values such that the minimum and maximum in each column are as given.
Z-score normalization (Gaussian): Linear transformation such that the values in each column are Gaussian-(0,1)-distributed, i.e. mean is 0.0 and standard deviation is 1.0.
Normalization by decimal scaling: The maximum value in a column (both positive and negative) is divided j-times by 10 until its absolute value is smaller or equal to 1. All values in the column are then divided by 10 to the power of j.

: Spark DataFrame/RDD with normalized columns.
: PMML document containing normalization parameters, which can be used in the "Spark Compiled Transformations Applier" node to normalize test data the same way as the training data has been normalized.

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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:

v4.4

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

Plugin provider: KNIME AG, Zurich, Switzerland

Plugin version: 4.4.1.v202108201127

On NodePit since: 2021-07-02

Last update: 2021-10-25

KNIME versions: Since v3.6