Node-RED This is a node-red wrapper for the GET and POST data retrieval and run prediction methods of the Watson Machine Learning service.
Use the manage palette option to install this node
This node allows you to run predictions against a deployed machine learning model.
To make a connection to your Watson Machine Learning service the node will need a connection configuration. Create a configuration by double selecting a node.
For most modes the node msg.payload
is not required. The node needs to be configured
to select model and deployment. A list of published models and deployments is
automatically retrieved by the node, making use of the API.
When running a prediction msg.payload
needs to be select either to an arrays of
an array of values, or an object containing and array of array of values,
against which to run predictions against.
eg. To run a prediction against a model expecting 6 decimal numbers.
msg.payload = [[16.4, 48.3, 30, 75.4, 28.9, 20]];
To run a prediction for multiple set of values
msg.payload = [[16.4, 48.3, 30, 75.4, 28.9, 20], [13.4, 38.3, 30, 75.4, 18.9, 25]];
or
msg.payload = {values : [[16.4, 48.3, 30, 75.4, 28.9, 20], [13.4, 38.3, 30, 75.4, 18.9, 25]] };
or
msg.payload = {"input_data":
[
{
"fields" :
["COLUMN1","COLUMN2","COLUMN3","COLUMN4","COLUMN5","COLUMN6"],
"values" :
[
[16.4, 48.3, 30, 75.4, 28.9, 20],
[2.99, 7.06, 70, 8.05, 87.7, 32]
]
}
]
};
in this way the fields parameter can also be provided.
For all modes
the output is a json object on msg.payload
.
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