Using Graph Kernels for Feature Generation - RapidMiner LOD extension

Created: 2015-05-04 18:11:04      Last updated: 2015-05-04 18:12:39

This example shows how to use graph kernels for feature generation.

In this example we use the Root RDF Walk Count Kernel, and the Fast RDF WL Sub Tree Kernel.

The input data for the process can be found here.

More information about the process can be found here.

Information Preview

Information Run

Not available

Information Workflow Components


Information Workflow Type


Information Uploader

Information License

All versions of this Workflow are licensed under:

Information Version 1 (of 1)

Information Credits (0)



Information Attributions (0)



Information Tags (0)


Log in to add Tags

Information Shared with Groups (0)


Information Featured In Packs (0)


Log in to add to one of your Packs

Information Attributed By (0)



Information Favourited By (0)

No one

Information Statistics


Citations (0)


Version History

In chronological order:

Reviews Reviews (0)

No reviews yet

Be the first to review!

Comments Comments (1)

Log in to make a comment

  • Monday 24 April 2017 09:09:52 (UTC)

    I tried to run this workflow, but I received an error message saying the setup has no obvious error, but the project seems not to work.

    The log reports the following error: SEVERE: java.lang.ArrayIndexOutOfBoundsException: 0.

    I did not find any manual for the RDF kernel operators, so I cannot fix this error. Any solution to suggest?

Workflow Other workflows that use similar services (0)

There are no workflows in myExperiment that use similar services to this Workflow.