20220707 Pikairos Machine learning based on signals or sets of descriptors

Some Machine Learning nodes in KNIME directly accept either fingerprints, Bit Vectors and Byte Vectors which are a kind of List data type in KNIME.

For instance, Random Forest, Tree Ensemble & Gradient Boosted nodes do. This is not however a feature that is implemented in all the KNIME ML learner nodes.

In your case, the values in the list seem to be integers. If the number of total values does not go beyond 256 (coded or renormalized from 0 to 255) then you could convert your columns into a “Byte Vector type” using the -Create Byte Vector- node (mind this is a special list type in KNIME and not exactly of type List) and then use it as input data for your classification learner.

Please find below an example where I’m converting 4 column descriptors into a Byte Vector of 4 values normalized between values 0 & 255:

I’m adding in a second row in my workflow example the usual way of using column descriptors for comparison.

Be aware that you would need to chose the “user fingerprint attribute” as “Attribute Selection” in the Learner node configuration dialog.

The example workflow is accessible from here:

20220707 Pikairos Machine learning based on signals or sets of descriptors.knwf (286.3 KB)

External resources

• Machine learning with signal