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I have a model opened within an Analysis and exported it to a jupyter notebook.
The model has one text feature that uses TF/IDF vectorization:
The model in the notebook is using TruncatedSVD/HashingVectorizer. This is the 'default' option in the model design page, i.e. the option gets selected when a text feature is added to a model:
But I changed that default option to TF/IDF vectorization as evident from the second image and trained the model.
I can modify the notebook and use tf-idf as designed.
But the question is whether it is possible to export a model the way it is designed?
Hi,
notebook generation to export a model only exports a "similar" model (documentation here: https://doc.dataiku.com/dss/latest/machine-learning/models-export.html#export-to-jupyter-notebook ). It is not possible to export the exact same model as the actual code might be much more complex than something that can fit in a human-editable notebook. The idea is to provide a good enough starting point that data scientists can actually build on.
Regards,
Joachim Zentici
Dataiku
Hi,
notebook generation to export a model only exports a "similar" model (documentation here: https://doc.dataiku.com/dss/latest/machine-learning/models-export.html#export-to-jupyter-notebook ). It is not possible to export the exact same model as the actual code might be much more complex than something that can fit in a human-editable notebook. The idea is to provide a good enough starting point that data scientists can actually build on.
Regards,
Joachim Zentici
Dataiku