How to use Python API to score a saved model
I have a trained model on my automation node. I have created an API key and in an externally running iPython Notebook attached to the saved model as thus:
client = DSSClient(host, apiKey)
sap = dataikuapi.dss.project.DSSProject(client, 'SIMPLEAFFINITYPLUS')
classifier_no_format = sap.get_saved_model('prediction_no_format')
Now, how can I score a single observation using this saved model? Extra points if I can score more than one observation in a single call.
Answers
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Hello,
The right way to do this is to use the API node, which is a lightweight dedicated node for scoring a single observation (or a couple of them). You create an API service in DSS with your python model, package it & import it into the API node, and you can score with a JSON API.
Check out the documentation: Real-time predictions.On the other hand, the DSS public API (of the design node & automation node) lets you control DSS itself: export data, change configuration, launch jobs, etc. but is not meant to be called for individual scoring.