Fig 1. Block diagram of Eq 29, showing how a workflow is created for each node.

The first step is one-hot encoding the data to embed it into ${\mathbb{R}}^M$. The next step computes the Mapper graph of the data. Then models are trained on each node, and summed. Finally, a decision function outputs the final class prediction.