In the second part of this series, we explore how the BigML Node-RED bindings work in more detail and introduce key concepts of input-output matching and node reification, which will allow you to create more complex flows. In this third and final part of this introductory series, we are going to review what we know about inputs and outputs in a more systematic way to introduce debugging facilities and present an advanced type of node that allows you to inject WhizzML code directly into your flows.
Details About Node Inputs and Outputs
Each BigML node has a varying number of inputs and outputs, which are embedded in the message payload that Node-RED propagates across nodes. For example, the ensemble node has one input called dataset and one output called ensemble. That means the following two things: