Synthetic Data Generator (Multilabel Classification)

This component generates example data for a multilabel classification task based on the make_multilabel_classification() function in the Python scikit-learn library.
It generates class columns with 0s/1s that indicate the absence/presence of the respective label. The average number of labels assigned to each row can be regulated.

For more information see the sklearn documentation:

scikit-learn.org/stable/modules/generated/sklearn.datasets.make_multilabel_classification.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

Output ports

1. Type: Table
   Port 1
   Multi-class Classification Data