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Hello,
Is there a way to automatically retrieve (via a recipe) features importances of a partitioned model, by partition, in DSS please ?
I tried to do it through a python recipe with the following code:
import dataiku
import pandas as pd
client = dataiku.api_client()
project = client.get_project(dataiku.default_project_key())
model = project.get_saved_model("BE8E0mVs")
perf = model.get_version_details('initial').get_raw().get("iperf")
But then perf is empty, I cannot do perf.retrieve("rawImportance") as suggested here. The code snippet works on an unpartitioned model though.
Thanks
Hi @julesbertrand ,
The get_predictor() and get_version_metrics() are not yet supported for partitioned models. We do have this feature request in our backlog.
Thanks,
Hi @julesbertrand ,
The get_predictor() and get_version_metrics() are not yet supported for partitioned models. We do have this feature request in our backlog.
Thanks,
I'd like to upvote the backlog enhancement for support of partitioned models in the API. Share the link to the enhancement request?