ML Model Node

Machine Learning Model Node

The ML Model node is the return point for data from the machine learning workbench. Models created or loaded in the machine learning workbench become available to the flow via this node.

The ML Model node will show all machine learning models available in a solution. It passes the input payload forward with output from the machine learning model.

Adding an ML Model node to your workflow

1. First, select your desired solution and navigate to Rayven Workflow.
2. Select ‘Machine Learning’ from the left-hand panel.
3. Find the ML Model node and drag it onto the canvas.
4. Provide input to the ML Model node by connecting it to your node of interest.
5. Double click on the ML Model node to open its configuration window.

Configuring your ML Model node

1. First, give your node a Name. Choose something simple that clearly explains its purpose.
2. Enter the name of the Machine Learning Model you want to return data from into the workflow. The drop-down menu will display all Machine Learning Models configured in the Machine Learning Workbench.
3. Enter a Data Field Name for a new field where you want to display the Machine Learning data.
4. Enter the variable to appear in this new field under Result to Field.

Once you have connected and saved your Go To node, it is ready to send data out of the workflow. Connect this node to a Visualization widget to display Machine Learning data.