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Spark SVD

KNIME Extension for Apache Spark core infrastructure version 4.3.1.v202101261633 by KNIME AG, Zurich, Switzerland

This node utilizes the Apache Spark Singular value decomposition (SVD) implementation.

Options

Number of leading singular values
The number of leading singular values to keep (0 < k <= n). It might return less than k if there are numerically zero singular values or there are not enough Ritz values converged before the maximum number of Arnoldi update iterations is reached (in case that matrix A is ill-conditioned).
Reciprocal condition number
The reciprocal condition number (rCond). All singular values smaller than rCond * sigma(0) are treated as zero, where sigma(0) is the largest singular value.
Compute U matrix
Select this option to compute the U matrix (left singular vectors).
Feature Columns
The feature columns to use during computation. Supports only numeric columns.

Input Ports

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Input Spark DataFrame/RDD

Output Ports

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The singular values vector.
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The right singular vectors.
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The left singular vectors.

Best Friends (Incoming)

Best Friends (Outgoing)

Installation

To use this node in KNIME, install KNIME Extension for Apache Spark from the following update site:

KNIME 4.3

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

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Developers

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