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non-zero exit status 1 #13
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You should re-run your code with debug on:
This will give you estimator and mapper Pickle files. Can you convert them using the JPMML-SkLearn command-line application? |
Thank you for the quick reply. Unfortunately, I am unable to convert the Pickle files when using the command-line. When running I get the error:
Is there a problem with the types I use? Every element should be either a float or integer. |
This exception is most likely the root cause of the above
It means that one of your Numpy arrays contains atypical Also, what are your Numpy and Python versions? Please paste the version information (as printed by |
Thank you for the reply. Here are my python and numpy versions. Furthermore, I just double-checked and the dtype of the elements in "data" is float64. As for the estimator and mapper Pickle files, I have emailed them to you. |
Upgraded my testing environment from Scikit-Learn 0.17.1 to 0.18. This exception now occurs with Python 2.7, but it doesn't occur with Python 3.4. So, as a temporary workaround, you might try downgrading to Scikit-Learn 0.17.1, or upgrading to Python 3.4. |
Unfortunately, I get the same error when using Python 2.7 and Python 3.4 with Scikit-Learn 0.17.1. Python 2.7 Versions: Python 2.7 Error:
Python 3.4 Versions: Python 3.4 Error:
Recreating the estimator and mapper Pickle files with Scikit-Learn 0.17.1 and manually converting it using the command-line returns the error:
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You can resolve
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It worked! Thank you very much! |
I'm reopening this issue, as I'm still working on the permanent fix. My testing shows that this |
I've released sklearn2pmml version 0.12.0, which should be able to handle Python 2.7 in combination with Scikit-Learn 0.18. At least I was able to convert your Pickle files. Anyway, I must warn you that if you're interested in evaluating your KNN models within JPMML/Openscoring software stack, then you'll be very likely disappointed with its performance. Your model contains 250k training instances, and during model scoring it will be necessary to select 400 of them (and average their predictions). Currently, JPMML/Openscoring performs the selection of closest training instances using brute-force scanning, which is clearly suboptimal here. |
I am also facing this issue now on Mac OS X, but due to a FileNotFoundError on the pkl path argument. I think it is trying to write the pkl in a temp folder ( EDIT: Actually the Pickle is there, it does fail in an IPython notebook though, but when I run the command from the debug afterwards in the terminal it does work ... |
I am currently attempting to transfer my sklearn model into a pmml file which will be read in a java program later on. My datasets have already gone through preprocessing so further transformations will not be very helpful. However, I keep receiving the error below even when I try different transformations.
The model seems to have been generated successfully and the output from the DataFrameMapper also seems correct. However, the error pops up when attempting to create and export the pmml file.
Code:
Error:
Weirdly enough, attempting to run the same code with Jupyter returns "OSError: [Errno 2] No such file or directory".
Any help or insight into the problem would be tremendously helpful!
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