Synthetic Data Generator (Regression)

This component generates example data for a regression task based on the make_regression() function in the Python scikit-learn library.It is possible to control the strength of the linear relationship by adding noise into the generated predictor features.

For more information see the sklearn documentation:

scikit-learn.org/stable/modules/generated/sklearn.datasets.make_regression.html

Note: This component requires a Python environment. In this blog post we explain how to setup the KNIME Python extension:

knime.com/blog/setting-up-the-knime-python-extension-revisited-for-python-30-and-20

Options

Amount of Noise
The standard deviation of the Gaussian noise applied to the generated features.
Number of Samples
The number of samples to generate.
Number of Features
The number of features to generate.
Random Seed
The seed for dataset creation to make the output reproducible.

Input Ports

This node has no input ports

Output Ports

Icon
Regression Data

Nodes

Extensions

Links

Download

To use this component in KNIME, download it from the below URL and open it in KNIME:

Download Component
On NodePit since: 2022-05-23
Last update: 2024-04-28
Created with KNIME version: v4.5.2

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