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Hi Apullin,
May i know how are you making the predictions currently? Here is how i manage to get probability of a class instead of only 0 or 1.
#Deploying
xgb_predictor = xgb.deploy(initial_instance_count=1,
instance_type='any')
#Serializer
xgb_predictor.serializer = sagemaker.serializers.CSVSerializer()
#Making the prediction
xgb_predictor.predict(array).decode('utf-8')]
You may try integrating this method into how you are performing 'batch transform' currently and see if it works.
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Also, do check that you did not use np.round() or anything similar on your response and hence converting the results to whole numbers.
Ah, I am using "batch prediction" through the web dashboard itself, via a CSV uploaded to S3. I am not at all familiar with the
boto3or thesagemakerpython APIs ... but maybe I'll have to try it out.Is there a way to do it from just the web interface?
For getting it to work in Python, I am up against a slightly different Sagemaker issue: The model (and many others) appear to exist in the output from Autopilot in Studio, but I don't know how to reference it outside of that context. I can "deploy" it to an endpoint, which is why I did the web batch transform.
Hi Apullin,
Noted that you are using the 'Create batch transform job' from SageMaker Console. I have tested the scenario using XGBoost Model for Binary Classification and is getting the probabilities. May i know what are the configurations you have set when creating the job?
OK, after some tinkering, I was able to run this in a Sagemaker Studio notebook:
But that still just gives back
0.0\n0.0\n1.0\n0.0\n....So, no idea. I suppose I'll go back to trying to do CV parameter search on XGBoost locally ... so much for AutoML.
One more note: While the "Model Details" view does give me a name for the model, that model does not seem to be actually accessible anywhere. That is, back in the web dashboard view, under "Inference >> Models", the long long list of models tried by AutoML do not exist there. It DOES give the path for an S3 bucket with a
model.tar.gzin it, though.Similarly, I am not able to reference that model via the
sagemakerpython, andListModelsonly shows me the same entries as on the web dashboard.