Comments (3)
Hi,
When I try to run elastic net in PiML, I can get an r2 value and other global interpretability metrics, but when I try to look at the influence of individual predictors, I see that the model has removed each predictor. When running code in sklearn that should give identical results, elastic net does not remove all of the predictors. I am not sure what is going on here. Perhaps it is some kind of bug?
Thank you
Hi @xloffree , Can you offer the code you used? Then I can do the test for answering your question. Thanks
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As you can see, I am running elastic net in PiML and sklearn. I should be getting the same results, or at the very least, PiML elastic net should not be removing every predictor.
from piml-toolbox.
Hi @xloffree,
Note that the data used by PiML is preprocessed to be within 0 and 1.
If you want to get the same results as sklearn's ElasticNest, please fit the model using the data preprocessed by PiML.
train_x, train_y, sample_weight_train = exp.get_data(train=True)
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